torch
Modules
Functions
- is_tensor - Checks whether the given object is a Tensor instance.
- is_floating_point - Checks whether a tensor has a floating-point data type.
- is_complex - Check if tensor has a complex numeric dtype.
- result_type - Returns the dtype that would result from an arithmetic operation
- is_autocast_cpu_enabled - Checks if automatic mixed precision is enabled for CPU operations.
- is_autocast_ipu_enabled - Checks if automatic mixed precision is enabled for IPU (Intel Processing Unit) operations.
- is_autocast_xla_enabled - Checks if automatic mixed precision is enabled for XLA (Tensor Compiler) operations.
- is_autocast_cache_enabled - Checks if the autocast cache is enabled.
- get_autocast_cpu_dtype - Returns the data type used by autocast for CPU operations.
- get_autocast_gpu_dtype - Returns the data type used by autocast for GPU (CUDA) operations.
- get_autocast_ipu_dtype - Returns the data type used by autocast for IPU operations.
- get_autocast_xla_dtype - Returns the data type used by autocast for XLA operations.
- clear_autocast_cache - Clears the autocast dtype and shape cache.
- autocast_increment_nesting - Increments the autocast nesting level.
- autocast_decrement_nesting - Decrements the autocast nesting level.
- is_anomaly_enabled - Checks if anomaly detection is enabled for gradient computation.
- is_anomaly_check_nan_enabled - Checks if anomaly detection specifically checks for NaN values in gradients.
- is_inference_mode_enabled - Checks if inference mode is enabled.
- get_num_threads - Returns the number of threads used for intra-op parallelism.
- get_num_interop_threads - Returns the number of threads used for inter-op parallelism.
- get_default_dtype - Returns the default data type used for newly created tensors.
- get_device_module - Returns the device module for the specified device type.
- get_rng_state - Returns the current random number generator state.
- profiler_allow_cudagraph_cupti_lazy_reinit_cuda12 - Allows CUDA graph lazy reinitialization for NVIDIA CUDA 12.
- compiled_with_cxx11_abi - Checks if torch.js was compiled with C++11 ABI compatibility.
- get_file_path - Returns the file path for a module or resource.
- use_deterministic_algorithms - Enables or disables deterministic algorithms for reproducibility.
- sym_float - Creates a symbolic float from a numeric value.
- sym_int - Creates a symbolic integer from a numeric value.
- sym_not - Creates the logical negation of a symbolic boolean value.
- createTorch - Creates the torch object with specific serialization implementations.
- get_default_device - Returns the current default device for tensor operations.
- set_default_device - Sets the default device for tensor creation operations.
- is_webgpu_available - Checks if WebGPU acceleration is available in the current environment.
- requireWebGPU - Assert that WebGPU is available for GPU-only operations.
- is_cpu_only_mode - Checks if the current environment is operating in CPU-only mode.
- validateDType - Runtime validation that a value is a valid DType.
- promote_types - Returns the lowest common dtype that can safely hold values from both input dtypes.
- is_floating_point_dtype - Checks if the given dtype is a floating-point type.
- is_complex_dtype - Checks if the given dtype is a complex number type.
- get_real_dtype - Get the underlying real dtype for a complex dtype.
- list_ops - List all registered operations.
- get_op_info - Get detailed information about an operation.
- list_dtypes - List all registered dtypes (built-in and custom).
- list_custom_dtypes - List only custom-registered dtypes (not built-in).
- has_dtype - Check if a dtype is registered (built-in or custom).
- get_dtype_info - Get detailed information about a dtype.
- list_kernels - List all registered kernels.
- has_kernel - Check if a kernel is registered for (op, dtype, device).
- has_autograd - Check if autograd is registered for an operation.
- list_functions - List all registered custom functions.
- list_methods - List all registered custom methods.
- coverage_report - Generate a coverage report for registered operations.
- register_backward - Register autograd with full configuration object.
- register_device - Register a custom device backend.
- initialize_device - Initialize a registered device.
- get_device_context - Get a registered device's context.
- get_device_config - Get a registered device's configuration.
- has_device - Check if a device is registered.
- list_devices - List all registered devices (both built-in and custom).
- list_custom_devices - List only custom registered devices.
- unregister_device - Unregister a custom device.
- register_dtype - Register a custom dtype with full configuration object.
- register_forward - Register a kernel with full configuration object.
- register_function - Register a custom function with full configuration object.
- register_method - Register a custom Tensor method with full configuration object.
- register_scalar_forward - Register a scalar operation kernel (tensor-scalar operations).
- relu - Applies the ReLU (Rectified Linear Unit) function element-wise.
- gelu - Applies the GELU (Gaussian Error Linear Unit) function element-wise.
- silu - Applies the SiLU (Sigmoid Linear Unit) / Swish function element-wise.
- leaky_relu - Applies the Leaky ReLU function element-wise.
- elu - Applies the ELU (Exponential Linear Unit) function element-wise.
- selu - Applies the SELU (Scaled Exponential Linear Unit) function element-wise.
- softplus - Applies the Softplus function element-wise.
- softsign - Applies the Softsign function element-wise.
- hardsigmoid - Applies the Hardsigmoid function element-wise.
- hardswish - Applies the Hardswish function element-wise.
- matmul - Matrix multiplication of two tensors (universal @ operator).
- mm - Performs matrix multiplication between two 2D tensors.
- bmm - Perform batched matrix-matrix multiplication.
- chain_matmul - Efficiently multiplies a sequence of matrices, optimizing for minimum computation cost.
- mv - Perform matrix-vector multiplication.
- dot - Computes the dot product of two 1D vectors.
- vdot - Compute the vector dot product with conjugation.
- outer - Computes the outer product of two 1D vectors.
- addmm - Performs fused matrix multiplication and addition: betainput + alpha(mat1 @ mat2).
- addmv - Performs fused matrix-vector multiplication and addition: betainput + alpha(mat @ vec).
- addr - Performs fused outer product and addition: betainput + alpha(vec1 ⊗ vec2).
- baddbmm - Performs fused batched matrix multiplication and addition: betainput + alpha(batch1 @ batch2).
- addbmm - Performs fused batched matrix multiplication, reduces batch dimension with sum, and adds: beta*input
- trapezoid - Integrates values along a dimension using the trapezoidal rule.
- cumulative_trapezoid - Computes the cumulative integral along a dimension using the trapezoidal rule.
- kron - Computes the Kronecker product of two tensors.
- tensordot - Computes generalized tensor contraction over specified dimensions.
- inverse - Computes the matrix inverse: A^(-1) such that A @ A^(-1) = I.
- cdist - Computes pairwise distances between two sets of vectors using various distance metrics.
- eq - Element-wise comparison of two tensors with a specified tolerance.
- ne - Element-wise inequality comparison: returns true where input != other.
- lt - Element-wise less-than comparison: returns true where input < other.
- le - Element-wise less-than-or-equal comparison: returns true where input <= other.
- gt - Element-wise greater-than comparison: returns true where input > other.
- ge - Element-wise greater-than-or-equal comparison: returns true where input >= other.
- isnan - Returns a boolean tensor indicating which elements are NaN (Not a Number).
- isinf - Returns a boolean tensor indicating which elements are +/- infinity.
- isfinite - Returns a boolean tensor indicating which elements are finite (valid numbers).
- isposinf - Returns a boolean tensor indicating which elements are positive infinity (+∞).
- isneginf - Returns a boolean tensor indicating which elements are negative infinity (-∞).
- isreal - Tests whether each element is a real-valued number (not complex).
- maximum - Computes element-wise maximum of two tensors.
- minimum - Computes element-wise minimum of two tensors.
- fmax - Computes element-wise maximum, ignoring NaN values.
- fmin - Computes element-wise minimum, ignoring NaN values.
- equal - Returns true if two tensors have the same size and elements, false otherwise.
- isclose - Element-wise tolerance-based comparison: returns true where input and other are close.
- allclose - Test if all elements are close (within tolerance): returns single boolean result.
- logical_not - Computes the element-wise logical NOT (negation).
- logical_and - Computes the element-wise logical AND.
- logical_or - Computes the element-wise logical OR.
- logical_xor - Computes the element-wise logical XOR (exclusive OR).
- bitwise_and - Element-wise bitwise AND: sets bit to 1 only where both operands have 1.
- bitwise_or - Element-wise bitwise OR: sets bit to 1 if either operand has 1.
- bitwise_xor - Element-wise bitwise XOR (exclusive OR): sets bit to 1 where operands differ.
- bitwise_not - Element-wise bitwise NOT (complement): inverts all bits of integers.
- bitwise_left_shift - Element-wise left bit shift: shifts bits left, filling with zeros.
- bitwise_right_shift - Element-wise right bit shift: shifts bits right, filling with zeros (unsigned) or sign (signed).
- sort - Sorts the elements of the input tensor along a given dimension in ascending order by value.
- argsort - Returns the indices that would sort a tensor along a given dimension.
- msort - Sorts the elements of the input tensor along its first dimension.
- topk - Returns the k largest elements of the given input tensor along a given dimension.
- kthvalue - Returns the k-th smallest element (by value) and its index along a dimension.
- isin - Tests if each element of input is in test_elements, returning a boolean tensor.
- view_as_complex - Interpret a real tensor as a complex tensor.
- view_as_real - Convert a complex tensor back to its real representation.
- polar - Reconstruct a complex tensor from its magnitude and phase angle (polar form).
- complex - Create a complex tensor from separate real and imaginary tensors.
- are_deterministic_algorithms_enabled - Check if deterministic algorithm mode is currently enabled.
- is_deterministic_algorithms_warn_only_enabled - Check if warn-only mode is enabled for non-deterministic operations.
- set_deterministic_debug_mode - Set the debug verbosity level for deterministic algorithm violations.
- get_deterministic_debug_mode - Get the current debug verbosity level for deterministic algorithm violations.
- set_warn_always - Enable or disable "always warn" mode for all warnings.
- is_warn_always_enabled - Check if "always warn" mode is currently enabled.
- set_float32_matmul_precision - Set the precision level for float32 matrix multiplications.
- get_float32_matmul_precision - Get the current float32 matrix multiplication precision level.
- set_printoptions - Configures how tensors are displayed when printed or logged.
- get_printoptions - Retrieves the current tensor print options.
- is_nonzero - Checks if a single-element tensor contains a non-zero value.
- set_default_tensor_type - Sets the default tensor type (deprecated - use dtype and device options instead).
- tensor - Create a tensor from array data.
- zeros - Create a tensor filled with zeros.
- ones - Create a tensor filled with ones.
- full - Create a tensor filled with a specific constant value.
- zeros_like - Create a zero-filled tensor with the same shape as another tensor.
- ones_like - Create a one-filled tensor with the same shape as another tensor.
- full_like - Create a constant-filled tensor with the same shape as another tensor.
- empty - Create a tensor with uninitialized memory.
- empty_like - Create an uninitialized tensor with the same shape as another tensor.
- rand - Create a tensor with random values from uniform distribution [0, 1).
- randn - Create a tensor with random values from standard normal distribution.
- randint - Create a tensor filled with random integers in [low, high).
- randint_like - Create a tensor with same shape as input filled with random integers.
- rand_like - Create a tensor with same shape as input filled with uniform random values.
- randn_like - Create a tensor with same shape as input filled with standard normal values.
- bernoulli - Draws independent binary random numbers from a Bernoulli distribution.
- randperm - Returns a random permutation of integers from 0 to n - 1.
- normal - Returns a tensor of random numbers from normal distribution.
- multinomial - Draws samples from a multinomial distribution (GPU accelerated).
- multinomial_async - Async version of multinomial sampling that supports sampling without replacement on GPU.
- poisson - Draws samples from a Poisson distribution with specified rate parameters.
- eye - Creates an identity matrix (or rectangular variant).
- arange - Create a tensor with values in a range.
- linspace - Create a tensor with linearly spaced values.
- logspace - Create a tensor with logarithmically spaced values.
- tril - Returns the lower triangular part of a 2D matrix (or batch of matrices).
- triu - Returns the upper triangular part of a 2D matrix.
- cat - Concatenates tensors along an existing dimension.
- stack - Concatenates a sequence of tensors along a new dimension.
- vstack - Stacks tensors vertically (row wise).
- hstack - Stacks tensors horizontally (column wise).
- dstack - Stacks tensors along the depth dimension (third axis).
- column_stack - Stacks 1-D arrays as columns into a 2-D array.
- as_tensor - Convert data to a tensor.
- frombuffer - Create a tensor from a buffer.
- meshgrid - Creates coordinate grids from 1-D tensors.
- tril_indices - Returns the row and column indices of the lower triangular part of a matrix.
- triu_indices - Returns the row and column indices of the upper triangular part of a matrix.
- combinations - Returns all r-length combinations of elements from the input tensor.
- cartesian_prod - Returns the Cartesian product of input tensors.
- clearEinopsCache - Clear the pattern cache (exported for testing)
- getEinopsCacheSize - Get pattern cache size (exported for testing)
- rearrange - Rearranges tensor dimensions using einops-style pattern notation.
- reduce - Reduce tensor dimensions with pattern syntax.
- repeat - Repeat tensor elements with pattern syntax.
- pack - Pack multiple tensors along a new dimension.
- unpack - Unpack a tensor into multiple tensors.
- clearEinsumCache - Clear the equation cache (exported for testing)
- getEinsumCacheSize - Get equation cache size (exported for testing)
- einsum - Sums the product of the elements of the input operands along dimensions
- levenshteinDistance - Shared error utilities for improved error messages.
- findSimilarPatterns - Find similar einsum patterns to the given equation.
- formatShape - Format a shape array for display.
- formatEquationError - Format an einsum equation with visual markers for errors.
- buildErrorMessage - Build a formatted multi-line error message.
- buildEinopsError - Build an einops-style error message.
- index_select - Selects elements from the input tensor along a dimension using indices.
- select - Selects a single element along a dimension by index, removing that dimension.
- where - Returns a tensor with elements chosen from input or other depending on condition.
- nonzero - Returns indices of all non-zero elements in a tensor.
- argwhere - Returns indices of all non-zero elements in a tensor.
- gather - Gathers values from input along a dimension using indices.
- take_along_dim - Gathers values using indices, with automatic broadcasting.
- scatter - Scatters values into a tensor at specified indices along a dimension.
- scatter_add - Scatters values into a tensor by adding at specified indices.
- scatter_reduce - Scatters values with custom reduction operation at specified indices.
- scatter_reduce_ - In-place version of scatter_reduce: applies reduction at indices in-place.
- scatter_add_ - In-place version of scatter_add: adds at specified indices in-place.
- index_add - Adds source elements to input at positions specified by 1D indices.
- index_reduce - Applies custom reduction operation at 1D index positions.
- index_put - Places values into a tensor at index positions (general indexing operation).
- diagonal_scatter - Scatters values along a diagonal in the tensor.
- select_scatter - Scatters a tensor at a single index position along a dimension.
- slice_scatter - Scatters values at a slice range along a dimension.
- take - Returns a new tensor with elements from input selected by the flat indices.
- index_copy - In-place version of scatter_reduce: applies reduction at indices in-place.
- index_fill - Fills positions specified by 1D indices with a scalar value.
- masked_select - Returns a 1D tensor containing elements from input where mask is True.
- masked_select_async - Async version of masked_select that returns a tensor with exact shape.
- flatten - Flattens a contiguous range of dimensions into a single dimension.
- squeeze - Removes dimensions of size 1 from the tensor.
- unsqueeze - Adds a dimension of size 1 at the specified position.
- broadcast_shapes - Computes the broadcast shape of multiple shapes.
- broadcast_tensors - Broadcasts tensors to a common shape.
- transpose - Swaps two dimensions of a tensor and returns a new tensor.
- swapaxes - Swaps two dimensions of the input tensor.
- adjoint - Returns a view of the tensor with the last two dimensions transposed.
- conj - Returns the complex conjugate of the input tensor.
- split - Splits a tensor into chunks of specified size along a dimension.
- chunk - Splits a tensor into a specified number of chunks along a dimension.
- narrow - Narrows a tensor along a dimension, extracting a contiguous slice.
- tensor_split - Splits a tensor into multiple sub-tensors along a dimension.
- hsplit - Splits input tensor into multiple tensors horizontally (column-wise).
- vsplit - Splits input tensor into multiple tensors vertically (row-wise).
- dsplit - Splits input tensor into multiple tensors depthwise (along the third axis).
- unbind - Removes a dimension and returns individual tensors along that dimension.
- unravel_index - Converts flat linear indices into multi-dimensional coordinate tensors.
- unflatten - Expands a dimension of the input tensor over multiple dimensions.
- roll - Rolls tensor elements along one or more dimensions.
- rot90 - Rotates tensor 90 degrees in a 2D plane.
- diff - Computes n-th order finite differences along a dimension.
- repeat_interleave - Repeats tensor elements a specified number of times along a dimension.
- clone - Creates a deep copy of the tensor.
- contiguous - Ensures tensor is contiguous in memory.
- detach - Detaches tensor from the autograd computational graph.
- expand - Expands singleton dimensions to match a target shape.
- view - Reshapes tensor to a different shape without changing data order.
- expand_as - Expands tensor to match shape of another tensor.
- numel - Returns the total number of elements in the tensor.
- as_strided - Creates a view of the input tensor with the given size and stride.
- atleast_1d - Returns a tensor with at least 1 dimension.
- atleast_2d - Returns a tensor with at least 2 dimensions.
- atleast_3d - Returns a tensor with at least 3 dimensions.
- reshape - Returns a tensor with the same data and number of elements as input, but with the specified shape.
- broadcast_to - Broadcasts input to a new shape.
- t - Expects input to be a matrix (2-D tensor) and transposes it.
- permute - Returns a view of the input tensor with its dimensions rearranged.
- movedim - Moves one or more dimensions of the input tensor to new positions.
- flip - Reverses the order of elements in a tensor along the specified dimensions.
- fliplr - Flips the tensor along dimension 1 (horizontal flip for 2D images).
- flipud - Flips the tensor along dimension 0 (vertical flip for 2D images).
- narrow_copy - Returns a copy of a narrowed version of the input tensor along a dimension.
- tile - Constructs a tensor by repeating the input tensor along specified dimensions.
- ravel - Returns a contiguous flattened 1D tensor.
- applyOut - Helper to copy result into out tensor if provided.
- logcumsumexp - Returns the logarithm of the cumulative summation of the exponentiation of elements.
- diag - Extracts the diagonal from a 2D tensor or constructs a diagonal matrix from a 1D tensor.
- block_diag - Create a block diagonal matrix from provided tensors.
- diag_embed - Creates a tensor whose diagonals of certain 2D planes are filled by input.
- diagflat - Creates a 2D tensor with the flattened input on the diagonal.
- searchsorted - Find the indices into a sorted sequence such that values would be inserted to maintain order.
- bucketize - Returns the indices of the buckets to which each value in the input belongs.
- bincount - Count the frequency of each value in an array of non-negative integers.
- histc - Computes the histogram of a tensor using fixed-width bins.
- histogram - Computes the histogram of a tensor with bin edges.
- sum - Returns the sum of all elements in the input tensor.
- mean - Returns the mean (average) of all elements in the input tensor.
- prod - Returns the product of all elements in the input tensor.
- std - Returns the standard deviation of all elements in the input tensor.
- var_ - Returns the variance of all elements in the input tensor.
- max - Returns the maximum value(s) and their indices along a dimension.
- min - Returns the minimum value of all elements in the input tensor.
- argmax - Returns the indices of the maximum value along a tensor dimension.
- argmin - Returns the indices of the minimum value along a tensor dimension.
- amax - Returns the maximum value along a dimension in the input tensor.
- amin - Returns the minimum value along a dimension in the input tensor.
- all - Tests if all elements in the input tensor evaluate to True.
- any - Tests if any element in the input tensor evaluates to True.
- logsumexp - Returns the log of summed exponentials along a dimension in a numerically stable way.
- dist - Returns the p-norm distance between two tensors: norm(input - other, p).
- aminmax - Returns both the minimum and maximum values of the input tensor.
- nansum - Returns the sum of all elements, treating NaN values as zero.
- nanmean - Computes the mean of all non-NaN elements.
- std_mean - Computes both the standard deviation and mean along a dimension.
- var_mean - Computes both the variance and mean along a dimension.
- count_nonzero - Counts the number of non-zero values in a tensor.
- norm - Computes the norm (vector length/magnitude) of a tensor.
- median - Returns the median value(s) of the input tensor.
- nanmedian - Returns the median of values, ignoring NaN values.
- mode - Returns the mode (most frequently occurring value) along a dimension.
- quantile - Computes the q-th quantiles of each row of the input tensor.
- nanquantile - Computes quantiles, ignoring NaN values.
- unique - Returns the unique elements of the input tensor.
- unique_consecutive - Returns the unique consecutive elements of the input tensor.
- cov - Estimates the covariance matrix of variables given observations.
- corrcoef - Computes the Pearson correlation coefficient matrix between variables.
- trace - Returns the trace (sum of diagonal elements) of a 2D matrix.
- abs - Computes the absolute value of each element in the input tensor.
- acos - Computes the inverse cosine (arc cosine) of each element in the input tensor.
- acosh - Computes the inverse hyperbolic cosine of each element in the input tensor.
- add - Adds a tensor or scalar to the input tensor element-wise.
- addcdiv - Performs element-wise division then adds to input:
result = input + value * (tensor1 / tensor2). - addcmul - Performs element-wise multiplication then adds to input: `result = input + value * (tensor1 * tensor
- angle - Returns the angle (argument) of complex tensor elements in the complex plane.
- asin - Computes the inverse sine (arc sine) of each element in the input tensor.
- asinh - Computes the inverse hyperbolic sine of each element in the input tensor.
- atan - Computes the inverse tangent (arc tangent) of each element in the input tensor.
- atan2 - Computes element-wise arctangent of input/other with quadrant awareness.
- atanh - Computes the inverse hyperbolic tangent of each element in the input tensor.
- ceil - Computes the ceiling of each element in the input tensor.
- clamp - Clamps each element to be within the specified range [min, max].
- conj_physical - Returns the element-wise complex conjugate of the input tensor.
- copysign - Returns a tensor with the magnitude of input and the sign of other element-wise.
- cos - Computes the cosine of each element in the input tensor.
- cosh - Computes the hyperbolic cosine of each element in the input tensor.
- createCumExtremeResult - Create a namedtuple-like result for cummax/cummin - exported for Tensor methods
- cummax - Returns the cumulative maximum along a dimension.
- cummin - Returns the cumulative minimum along a dimension.
- cumprod - Returns the cumulative product along a dimension.
- cumsum - Returns the cumulative sum along a dimension.
- deg2rad - Converts angles from degrees to radians element-wise.
- digamma - Computes the logarithmic derivative of the gamma function (psi function).
- div - Divides the input tensor by another tensor or scalar element-wise.
- erf - Computes the error function of each element in the input tensor.
- erfc - Computes the complementary error function of each element in the input tensor.
- erfinv - Computes the inverse error function of each element in the input tensor.
- exp - Computes the exponential of each element in the input tensor.
- exp2 - Computes 2^x for each element in the input tensor.
- expm1 - Computes exp(x) - 1 element-wise. More accurate than exp(x) - 1 for small x.
- float_power - Raises input to the power of exponent using double precision arithmetic.
- floor - Computes the floor of each element in the input tensor.
- floor_divide - Computes element-wise floor division (integer division rounded toward negative infinity).
- fmod - Computes C-style modulo element-wise (result has same sign as dividend).
- frac - Computes the fractional part of each element in the input tensor.
- frexp - Decomposes input into mantissa and exponent tensors such that input = mantissa * 2^exponent.
- gcd - Computes the element-wise greatest common divisor (GCD) of two tensors.
- heaviside - Computes the Heaviside step function element-wise.
- registerBinaryOp - Register a binary operation with minimal boilerplate.
- registerUnaryOp - Register a unary operation with minimal boilerplate.
- hypot - Computes the hypotenuse (Euclidean distance) element-wise: sqrt(x^2 + y^2).
- i0 - Computes the zeroth order modified Bessel function of the first kind.
- imag - Extracts the imaginary component from a tensor of complex numbers.
- lcm - Computes the element-wise least common multiple (LCM) of two tensors.
- ldexp - Computes input * 2^other element-wise.
- lerp - Linear interpolation between start and end tensors.
- lgamma - Computes the natural logarithm of the absolute value of the gamma function.
- log - Computes the natural logarithm of each element in the input tensor.
- log10 - Computes the base-10 logarithm of each element in the input tensor.
- log1p - Computes log(1 + x) element-wise. More accurate than log(1 + x) for small x.
- log2 - Computes the base-2 logarithm of each element in the input tensor.
- logaddexp - Computes log(exp(x) + exp(y)) element-wise in a numerically stable way.
- logaddexp2 - Computes log2(2^x + 2^y) element-wise in a numerically stable way.
- masked_fill - Fills elements of input tensor with value where mask is True.
- mul - Multiplies two tensors or a tensor and scalar element-wise.
- nan_to_num - Replaces NaN, positive infinity, and negative infinity with specified values.
- neg - Computes the element-wise negation of the input tensor.
- nextafter - Returns the next representable floating-point value after input towards other.
- celu - Implementation of CELU activation.
- dropout - Implementation of dropout.
- elu_ - In-place ELU activation function.
- glu - Implementation of GLU activation.
- hardshrink - Implementation of hardshrink activation.
- hardtanh_ - In-place version of hardtanh.
- hardtanh - HardTanh activation function: clamps values to bounded range.
- leaky_relu_ - In-place Leaky ReLU activation function.
- linear - Implementation of linear transformation.
- log_softmax - Implementation of log_softmax.
- logsigmoid - Implementation of LogSigmoid activation.
- mish - Implementation of Mish activation.
- prelu - Implementation of PReLU activation.
- relu_ - In-place ReLU activation function.
- relu6 - Implementation of ReLU6 activation.
- rrelu - Implementation of RReLU activation.
- rrelu_ - In-place version of rrelu.
- sigmoid - Sigmoid activation function.
- softmax - Implementation of softmax.
- softmin - Implementation of softmin activation.
- softshrink - Implementation of softshrink activation.
- tanh - Tanh activation function.
- tanhshrink - Implementation of tanhshrink activation.
- threshold - Implementation of threshold activation.
- threshold_ - In-place threshold activation.
- positive - Returns the input tensor unchanged. This is the unary + operator.
- pow - Raises the input tensor to the power of the exponent element-wise.
- rad2deg - Converts angles from radians to degrees element-wise.
- real - Extracts the real component from a tensor of complex numbers.
- reciprocal - Computes the element-wise reciprocal of the input tensor.
- remainder - Computes Python-style remainder element-wise (result has same sign as divisor).
- round - Rounds each element in the input tensor to the nearest integer.
- rsqrt - Computes the reciprocal of the square root of each element in the input tensor.
- sign - Returns the sign of each element: -1 for negative, 0 for zero, 1 for positive.
- signbit - Tests if each element has its sign bit set (is negative or -0).
- sin - Computes the sine of each element in the input tensor.
- sinc - Computes the normalized sinc function of each element in the input tensor.
- sinh - Computes the hyperbolic sine of each element in the input tensor.
- sqrt - Computes the square root of each element in the input tensor.
- square - Implementation of square activation.
- sub - Subtracts a tensor or scalar from the input tensor element-wise.
- tan - Computes the tangent of each element in the input tensor.
- true_divide - Divides input by other, always producing floating-point output.
- trunc - Truncates each element towards zero (removing fractional part).
- xlogy - Computes x * log(y) element-wise, returning 0 when x is 0.
- hann_window - Hann (Hanning) window: symmetric window with zero endpoints for spectral analysis.
- hamming_window - Hamming window: cosine window with optimized coefficients for low side lobes.
- blackman_window - Blackman window: excellent side lobe suppression at cost of wider main lobe.
- bartlett_window - Bartlett window: simple triangular window with moderate performance.
- kaiser_window - Kaiser window: tunable window with parametric control over frequency/sidelobe tradeoff.
- fft - Computes the 1D discrete Fourier Transform (FFT) of a signal.
- ifft - Computes the 1D inverse discrete Fourier Transform (IFFT) of a signal.
- rfft - Computes the 1D FFT of a real-valued input signal (one-sided spectrum).
- irfft - Computes the 1D inverse FFT of a one-sided real FFT result.
- stft - Computes the Short-Time Fourier Transform (STFT) of a signal.
- istft - Inverse Short-time Fourier Transform.
- vmap - vmap is the vectorizing map;
vmap(func)returns a new function that - validateDevice - Validates that a value is a valid DeviceType at runtime.
- broadcastShapes - Broadcasting utilities for tensor operations.
- needsBroadcast - Check if shapeA needs broadcasting to match shapeB.
- canBroadcastTo - Check if a shape is broadcastable to a target shape.
- memory_stats - Returns memory statistics from the WebGPU buffer allocator.
- memory_summary - Returns a human-readable summary of WebGPU memory usage.
- empty_cache - Releases all unoccupied cached memory from the allocator.
- reset_peak_memory_stats - Resets the peak memory statistics counter.
KernelRegistry
- registerKernel - Register a kernel for (op, dtype, device).
- getKernel - Get a kernel for (op, dtype, device).
- hasKernel - Check if a kernel exists for (op, dtype, device).
- findKernelWithPredicate - Find a kernel that matches the predicate, if any.
- registerScalarKernel - Register a scalar kernel for (op, dtype, device).
- getScalarKernel - Get a scalar kernel for (op, dtype, device).
- hasScalarKernel - Check if a scalar kernel exists for (op, dtype, device).
- registerAutograd - Register autograd for an operation.
- getAutograd - Get autograd for (op, dtype, device).
- hasAutograd - Check if autograd is registered for (op, dtype, device).
- registerDType - Register a custom dtype.
- getDType - Get dtype info.
- hasDType - Check if a dtype is registered.
- listCustomDTypes - List all registered custom dtypes.
- registerFunction - Register a custom function.
- getFunction - Get a registered function.
- hasFunction - Check if a function is registered.
- registerMethod - Register a custom method.
- getMethod - Get a registered method.
- hasMethod - Check if a method is registered.
- listOps - List all registered operations.
- listDTypes - List all registered dtypes (both built-in and custom).
- listKernels - List all registered kernels.
- getOpInfo - Get info about a specific operation.
- coverageReport - Generate coverage report.
- listFunctions - List all registered functions.
- listMethods - List all registered methods.
Types
- DeterministicOptions - Options for use_deterministic_algorithms
- Torch - The torch module type with all operations and sub-modules.
- DeviceType - Device management for automatic CPU fallback.
- DType - Supported data types for tensors.
- TypedArray - Union type of all supported TypedArray types for CPU tensor storage.
- TensorLike - Tensor type placeholder.
- GradientsFor - Derive gradient return type from operation schema.
- InputsFor - Derive input type from operation schema.
- GradContext - Context for gradient computation.
- SetupContextFn - Setup context function type.
- BackwardFn - Backward function type.
- AutogradDevice - Device type for autograd registration.
- AutogradDType - DType type for autograd registration.
- AutogradConfig - Autograd configuration for an operation.
- AutogradEntry - Internal autograd entry stored in registry.
- BufferUsage - Usage flags for device buffers.
- DeviceBuffer - Abstract device buffer interface.
- DispatchConfig - Configuration for dispatching a compute operation.
- DeviceContext - Device context returned from initialization.
- DeviceCapabilities - Device capabilities.
- DeviceConfig - Configuration for registering a custom device.
- DeviceEntry - Internal device entry stored in registry.
- TupleOfLength - Create a tuple type of specific length.
- DTypeComponents - Registry of dtype component information.
- DTypeRegistry - Registry of all dtype names.
- RegisteredDType - Union of all registered dtype names.
- DTypeSerializationConfig - Serialization configuration for custom dtypes.
- DTypeDisplayConfig - Display configuration for custom dtypes.
- DTypeConfig - Configuration for registering a custom dtype.
- DTypeEntry - Internal dtype entry stored in registry.
- IsRegistryError - Check if a type is a registry error.
- AssertNotError - Assert that a type is not a registry error.
- op_not_found_error - Error: Operation not found in registry.
- op_kind_mismatch_error - Error: Invalid operation kind.
- dtype_not_found_error - Error: DType not found in registry.
- dtype_components_mismatch_error - Error: DType components mismatch.
- dtype_already_registered_error - Error: DType already registered.
- kernel_not_registered_error - Error: Kernel not registered.
- kernel_signature_mismatch_error - Error: Kernel signature mismatch.
- autograd_not_registered_error - Error: Autograd not registered.
- autograd_gradient_mismatch_error - Error: Autograd gradient shape mismatch.
- function_already_registered_error - Error: Function already registered.
- method_already_registered_error - Error: Method already registered.
- method_dtype_not_supported_error - Error: Method dtype restriction violated.
- invalid_config_error - Error: Invalid configuration.
- registration_failed_error - Error: Registration failed.
- DTypeInfo - Information about a registered dtype.
- DTypeCoverageReport - Get a coverage report filtered by dtype.
- TypedArrayFor - Map DType to its corresponding TypedArray type.
- BinaryKernelCPU - CPU kernel signature for binary operations.
- UnaryKernelCPU - CPU kernel signature for unary operations.
- ReductionKernelCPU - CPU kernel signature for reduction operations.
- KernelWebGPU - WebGPU kernel configuration.
- TensorMeta - Tensor metadata for predicate functions.
- KernelPredicate - Predicate function to determine if a kernel should be used.
- BaseKernelConfig - Base kernel configuration options.
- BinaryKernelConfigCPU - CPU kernel configuration for binary operations.
- UnaryKernelConfigCPU - CPU kernel configuration for unary operations.
- ReductionKernelConfigCPU - CPU kernel configuration for reduction operations.
- KernelConfigWebGPU - WebGPU kernel configuration.
- KernelConfig - Conditional kernel config type based on operation schema and device.
- CPUKernelEntry - CPU kernel entry stored in registry.
- KernelEntry - Internal kernel entry stored in registry.
- OpSchemas - Central registry of all operation schemas.
- OpName - Union of all operation names.
- GetOpSchema - Get the schema for a specific operation.
- GetOpKind - Get the kind of an operation ('binary', 'unary', 'reduction', etc.).
- IsBinaryOpName - Check if an operation is a binary operation.
- IsUnaryOpName - Check if an operation is a unary operation.
- IsReductionOpName - Check if an operation is a reduction operation.
- BinaryOpNames - Filter operation names to only binary operations.
- UnaryOpNames - Filter operation names to only unary operations.
- ReductionOpNames - Filter operation names to only reduction operations.
- RegisterBackwardOptions - Options for register_backward.
- RegisterDTypeOptions - Options for register_dtype.
- CPUForwardFn - CPU kernel forward function signature.
- CPUKernelConfig - CPU kernel configuration.
- WebGPUKernelConfig - WebGPU kernel configuration.
- RegisterKernelOptions - Common kernel registration options.
- RegisterFunctionOptions - Options for register_function.
- FunctionConfig - Full function configuration.
- RegisterMethodOptions - Options for register_method.
- MethodConfig - Full method configuration.
- ScalarCPUForwardFn - CPU scalar kernel forward function signature.
- ScalarCPUKernelConfig - CPU scalar kernel configuration.
- ScalarWebGPUKernelConfig - WebGPU scalar kernel configuration.
- ScalarKernelEntry - Scalar kernel entry stored in registry.
- FunctionEntry - Information about a registered function.
- MethodEntry - Information about a registered method.
- KernelInfo - Information about a registered kernel.
- OpInfo - Information about a registered operation.
- ListOpsOptions - Options for listing operations.
- ListKernelsOptions - Options for listing kernels.
- CoverageReport - Coverage report for registered operations.
- OpCoverageEntry - Coverage entry for a single operation.
- DeviceRegistry - Core type definitions for the torch.library extensibility system.
- Device - Union of all registered device types.
- IdentityShape - Identity shape rule - output has same shape as input.
- BroadcastShapeRule - Broadcast shape rule - shapes are broadcast together.
- MatmulShapeRule - Matrix multiplication shape rule.
- MMShapeRule - Matrix-matrix multiplication shape rule.
- SameShapeRule - Same shape rule - both inputs must have identical shape.
- ReductionShapeRule - Reduction shape rule - reduces along dimensions.
- DotShapeRule - Dot product shape rule.
- MVShapeRule - Matrix-vector multiplication shape rule.
- ShapeRule - Union of all shape rules.
- SameDTypeRule - Output dtype is same as input dtype.
- PromoteDTypeRule - Output dtype is promoted according to promotion rules.
- BooleanDTypeRule - Output dtype is always boolean.
- FloatDTypeRule - Output dtype is always float.
- DTypeRule - Union of all dtype rules.
- BinaryOpSchema - Schema for binary operations (two inputs, one output).
- UnaryOpSchema - Schema for unary operations (one input, one output).
- UnaryOpParams - Helper type to extract params from a UnaryOpSchema.
- ReductionOpSchema - Schema for reduction operations.
- CreationOpSchema - Schema for creation operations.
- ShapeOpSchema - Schema for shape operations.
- OpSchema - Union of all operation schema types.
- OpKind - Extract the kind from an operation schema.
- IsBinaryOp - Check if an operation schema is binary.
- IsUnaryOp - Check if an operation schema is unary.
- IsReductionOp - Check if an operation schema is a reduction.
- AddmmOptions - Options for addmm operation: out = beta * input + alpha * (mat1 @ mat2)
- AddmvOptions - Options for addmv operation: out = beta * input + alpha * (mat @ vec)
- AddrOptions - Options for addr operation: out = beta * input + alpha * (vec1 ⊗ vec2)
- BaddbmmOptions - Options for baddbmm operation: out = beta * input + alpha * (batch1 @ batch2)
- AddbmmOptions - Options for addbmm operation
- TensordotOptions - Options for tensordot
- CdistOptions - Options for cdist
- PrintOptions - Options for set_printoptions.
- EyeOptions - Options for torch.eye().
- RandintOptions - Options for randint
- RandintLikeOptions - Options for randint_like
- RandomLikeOptions - Options for rand_like and randn_like
- NormalOptions - Options for normal creation
- MultinomialOptions - Options for multinomial sampling
- MultinomialAsyncOptions - Options for async multinomial sampling
- TriOptions - Options for tril and triu
- CatOptions - Options for cat
- StackOptions - Options for stack
- IndicesOptions - Options for tril_indices and triu_indices
- CombinationsOptions - Options for combinations
- einops_error_invalid_pattern - Error: Pattern must contain exactly one '->'.
- einops_error_dimension_mismatch - Error: Input pattern dimension count doesn't match tensor rank.
- einops_error_undefined_axis - Error: Output axis not defined in input.
- einops_error_ambiguous_decomposition - Error: Cannot infer multiple unknown axes in composite.
- einops_error_anonymous_in_output - Error: Anonymous dimension (_) cannot be used in output pattern.
- RearrangeShape -
- ValidatedRearrangeShape - Validated shape that always extends readonly number[].
- einops_error_reduce_undefined_output - Error: Reduce pattern output must be subset of input axes.
- ReduceShape - Compute the output shape of a reduce operation.
- ValidatedReduceShape - Validated reduce shape.
- einops_error_repeat_missing_size - Error: Repeat requires axis size for new dimension.
- AxesRecord - Axes record type for repeat function.
- RepeatShape - Compute the output shape of a repeat operation.
- ValidatedRepeatShape - Validated repeat shape.
- PackShape - Compute pack output shape based on pattern.
- UnpackShape - Compute unpack output shape based on pattern.
- RearrangeOptions - Options for rearrange
- ReduceOptions - Options for reduce
- RepeatOptions - Options for repeat
- ReduceOperation - Reduction operations supported by einops.reduce.
- Ellipsis - Sentinel symbol representing ellipsis (...) in einsum sublist notation.
- SubscriptIndex - Valid subscript index for einsum sublist notation.
- SublistElement - Valid element in an einsum sublist.
- Sublist - A sublist of dimension specifications for einsum.
- EinsumOutputShape - Infer einsum output shape from equation and input shapes.
- einsum_error_operand_count_mismatch - Error: operand count doesn't match equation
- einsum_error_subscript_rank_mismatch - Error: subscript length doesn't match tensor rank
- einsum_error_invalid_equation - Error: invalid equation format
- einsum_error_unknown_output_index - Error: output subscript contains unknown index
- einsum_error_dimension_mismatch - Error: dimension size mismatch for repeated index
- einsum_error_index_out_of_range - Error: sublist index out of range
- einsum_error_invalid_sublist_element - Error: invalid element in sublist
- ValidateOperandCount - Validate that the number of operands matches the equation.
- ValidateRanks - Validate that all operand ranks match their subscripts.
- ValidateEinsum - Combined validation for einsum.
- ValidatedEinsumShape - Validated einsum output shape.
- EinsumOptions - Options for einsum operations
- TakeAlongDimOptions - Options for take_along_dim.
- DiagonalScatterOptions - Options for diagonal_scatter.
- NonzeroOptions - Options for nonzero operation
- SplitOptions - Options for split
- ChunkOptions - Options for chunk
- UnbindOptions - Options for unbind
- RollOptions - Options for roll
- Rot90Options - Options for rot90 operations
- DiffOptions - Options for diff
- RepeatInterleaveOptions - Options for repeat_interleave
- AsStridedOptions - Options for as_strided operations
- CumulativeOptions - Options for cumulative operations (cumsum, cumprod)
- CumulativeOptionsWithDim - Options for cumulative operations when dim is passed in options object
- DiagOptions - Options for diag.
- AddcdivOptions - Options for addcdiv operation: input + value * tensor1 / tensor2
- AddcmulOptions - Options for addcmul operation: input + value * tensor1 * tensor2
- BinaryOptions - Options for binary operations that support out parameter
- UnaryOptions - Options for unary operations that support out parameter
- DiagEmbedOptions - Options for diag_embed operations
- DiagFlatOptions - Options for diagflat operations
- SearchSortedOptions - Options for searchsorted operations
- BucketizeOptions - Options for bucketize operations
- BincountOptions - Options for bincount operations
- HistcOptions - Options for histc operations
- HistogramResult - Result type for histogram operation
- HistogramOptions - Options for histogram operations
- ReductionOptions - Options for sum, mean, prod operations
- StdVarOptions - Options for std and var operations
- StdVarMeanOptions - Options for std_mean and var_mean operations
- NormOptions - Options for norm operation
- LogsumexpOptions - Options for logsumexp.
- DistOptions - Options for dist.
- AminmaxOptions - Options for aminmax.
- NanReductionOptions - Options for nansum and nanmean.
- CountNonzeroOptions - Options for count_nonzero.
- QuantileOptions - Options for quantile operations
- UniqueOptions - Options for unique operations
- UniqueConsecutiveOptions - Options for unique_consecutive operations
- CovOptions - Options for covariance operations
- CumExtremeResult - Return type for cummax and cummin operations - supports both array and named access
- BinaryDType - Supported dtypes for binary operations.
- BinaryBackwardFn - Backward function for binary ops.
- BinaryOpConfig - Configuration for registering a binary operation.
- UnaryDType - Supported dtypes for unary operations.
- SaveForBackward - What to save for backward pass.
- UnaryBackwardFn - Backward function for unary ops.
- UnaryOpConfig - Configuration for registering a unary operation.
- UnaryOpFn - The function type returned by registerUnaryOp.
- CeluFunctionalOptions - Options for celu functional operation.
- DropoutFunctionalOptions - Options for dropout functional operation.
- EluFunctionalOptions - Options for elu functional operation.
- GluFunctionalOptions - Options for glu functional operation.
- HardtanhFunctionalOptions - Options for hardtanh functional operation.
- LeakyReluFunctionalOptions - Options for leaky_relu functional operation.
- ReluFunctionalOptions - Options for relu functional operation.
- RreluFunctionalOptions - Options for rrelu functional operation.
- SoftminFunctionalOptions - Options for softmin functional operation.
- SoftplusFunctionalOptions - Options for softplus functional operation.
- WindowOptions - Options for window functions.
- KaiserWindowOptions - Options for Kaiser window.
- FFTOptions - Options for FFT operations.
- STFTOptions - Short-time Fourier Transform.
- ISTFTOptions - Computes the inverse Short-Time Fourier Transform (ISTFT).
- Shape - Type-level shape computation for compile-time shape checking.
- DynamicShape - A dynamic shape (runtime-determined).
- Rank - Get the number of dimensions (rank) from a shape.
- At - Get element at index from tuple.
- Half - Divide a number by 2 (lookup table for common sizes).
- Double - Multiply a number by 2 (lookup table for common sizes).
- Triple - Multiply a number by 3 (lookup table for common sizes).
- MultiplyBy - Multiply a dimension by a factor.
- NegativeDim - Convert negative dimension to positive.
- IsShapeError - Check if a type is a shape error (not a valid Shape).
- ShapeErrorMessage - Extract the error message from a shape error type as a string literal.
- matmul_error_inner_dimensions_do_not_match - Matmul inner dimension mismatch error.
- batch_dimensions_do_not_match_error - Batch dimension mismatch error.
- transpose_error_requires_2d_tensor - Transpose requires 2D tensor error.
- broadcast_error_incompatible_dimensions - Broadcast dimension incompatibility error.
- dimension_error_out_of_range - Dimension out of range error.
- permute_error_dimension_count_mismatch - Permute dimension count mismatch error.
- expand_error_incompatible - Expand incompatible shape error.
- slice_error_out_of_bounds - Slice range error.
- narrow_error_start_out_of_bounds - Narrow start out of bounds error.
- narrow_error_length_exceeds_bounds - Narrow length exceeds bounds error.
- embedding_bag_error_requires_2d_input - Embedding bag requires 2D input error.
- Is2D - Check if a shape is 2D (for embedding_bag).
- IsAtLeast1D - Type guard to check if a shape is at least 1-dimensional (not a scalar).
- device_error_requires - Device error for operations that require a specific device.
- ValidateDevice - Check if device is valid for an operation.
- DeviceCheckedResult - Result type that checks device compatibility before returning the result.
- CPUOnlyResult - Shorthand for CPU-only operation result.
- WebGPUOnlyResult - Shorthand for WebGPU-only operation result.
- CheckShapeError - Check if a shape is an error shape.
- ShapeCheckedResult - Wraps a result type to check for shape errors in the result shape.
- BinaryBroadcastResult - Result type for binary broadcast operations (add, sub, mul, div).
- BroadcastShape - Compute broadcast shape for binary operations.
- MatmulShape - Compute output shape of matmul with various input dimensions.
- Matmul2DShape - Compute output shape of 2D matrix multiplication (strict).
- TransposeShape - Compute output shape of 2D transpose (.t()).
- MatrixTransposeShape - Compute output shape of matrix transpose (.mT, .mH).
- OuterShape - Compute output shape of outer product.
- TransposeDimsShape - Compute output shape of transpose(dim0, dim1).
- PermuteShape - Apply permutation to shape.
- RemoveDim - Remove a dimension from shape.
- select_error_index_out_of_bounds - Select index out of bounds error.
- SelectShape - Compute output shape of select operation with compile-time bounds checking.
- ReplaceDim - Replace dimension at index with new size.
- NarrowShape - Compute output shape of narrow operation with compile-time bounds checking.
- SliceShape - Compute output shape of index operation with a range.
- RangeSpec - Range specification for tensor slicing in the
.at()method. - MaskSpec - Marker type for boolean mask tensors in indexing.
- IndicesSpec - Marker type for index tensors in indexing.
- IndexSpec - Index specification for a single dimension in .at() calls.
- at_error_index_out_of_bounds - Index out of bounds error for .at() indexing.
- AtShape - Compute output shape of .at() multi-dimensional indexing.
- CumShape - Compute output shape of cumulative operations (cumsum, cumprod) with bounds checking.
- transpose_dims_error_out_of_range - Transpose dimension out of range error.
- TransposeDimsShapeChecked - Compute output shape of transpose(dim0, dim1) with bounds checking.
- flip_error_dim_out_of_range - Flip dimension out of range error.
- FlipShape - Compute output shape of flip operation with bounds checking.
- split_error_dim_out_of_range - Split dimension out of range error.
- chunk_error_dim_out_of_range - Chunk dimension out of range error.
- unbind_error_dim_out_of_range - Unbind dimension out of range error.
- ValidateSplitDim - Validate split dimension is within bounds.
- ValidateChunkDim - Validate chunk dimension is within bounds.
- ValidateUnbindDim - Validate unbind dimension is within bounds.
- gather_error_dim_out_of_range - Gather dimension out of range error.
- scatter_error_dim_out_of_range - Scatter dimension out of range error.
- index_select_error_dim_out_of_range - Index select dimension out of range error.
- GatherShape - Validate gather dim is within bounds and compute output shape.
- ScatterShape - Validate scatter dim is within bounds.
- IndexSelectShape - Compute output shape of index_select with bounds checking.
- softmax_error_dim_out_of_range - Softmax dimension out of range error.
- SoftmaxShape - Compute output shape of softmax with bounds checking.
- linalg_error_not_square_matrix - Error for operations requiring square matrices.
- linalg_error_requires_2d - Error for operations requiring 2D input.
- linalg_error_requires_at_least_2d - Error for operations requiring at least 2D input.
- ValidateSquareMatrix - Validate shape is a 2D square matrix.
- ValidateBatchedSquareMatrix - Validate shape is at least 2D with square last two dimensions (for batched linalg).
- CholeskyShape - Output shape of Cholesky decomposition.
- InverseShape - Output shape of matrix inverse.
- DetShape - Output shape of determinant.
- TraceShape - Output shape of trace.
- LUShape - Output shape of LU decomposition.
- SVDShape - Output shape of SVD.
- EigShape - Output shape of eigenvalue decomposition.
- item_error_not_scalar - Error for item() called on non-scalar tensor.
- ValidateScalar - Validate that a shape is a scalar (empty tuple).
- ItemResult - Type annotation for item() return that preserves assignability.
- DiagShape - Compute output shape of diag operation.
- TileShape - Alias for RepeatShape (tile and repeat have the same semantics).
- ExpandShape - Compute output shape of expand operation.
- SafeExpandShape - Safe version of ExpandShape that returns DynamicShape on error instead of error type.
- SqueezeShape - Compute output shape of squeeze.
- UnsqueezeShape - Compute output shape of unsqueeze.
- ReshapeShape - Compute output shape of reshape operation.
- FlattenShape - Compute output shape of flatten.
- InsertDim - Insert a dimension of given size at the specified position.
- StackShape - Compute output shape of stack operation.
- HalfDim - Halve a dimension in a shape (for GLU).
- DoubleDim - Double a dimension in a shape (for repeat_interleave with single repeat).
- ScaleDim - Scale (multiply) a dimension by a factor.
- CatShape - Compute output shape of concatenation along a dimension.
- Pool1dShape - Output shape for 1D pooling (input: [B, C, L] or [C, L]).
- Pool2dShape - Output shape for 2D pooling (input: [B, C, H, W] or [C, H, W]).
- Pool3dShape - Output shape for 3D pooling (input: [B, C, D, H, W] or [C, D, H, W]).
- AdaptivePool2dShape - Output shape for adaptive pooling that targets a specific output size.
- AdaptivePool1dShape - Output shape for adaptive 1D pooling.
- Conv1dShape - Output shape for 1D convolution.
- Conv2dShape - Output shape for 2D convolution.
- Conv3dShape - Output shape for 3D convolution.
- ConvTranspose2dShape - Output shape for transposed convolution (deconvolution).
- HasShapeError - Check if a shape is an error type.
- AssertNoShapeError - Assert that a shape is NOT an error.
- ShapedTensor - A tensor with compile-time shape information.
- TensorCreator - Type for tensor creation with variadic shape args.
- DeviceOptions - Options for Device constructor
- DeviceInput - Device input type - can be string, Device object, or device type.
- GradFn - Gradient function for autograd.
- TensorOptions - Options for tensor creation with compile-time dtype and device tracking.
- TypedStorage - Typed array storage for CPU tensors.
- TensorStorage - Discriminated union for tensor storage across devices.
- WebGPUTensorData - Internal tensor data structure for WebGPU tensors.
- CPUTensorData - Internal tensor data structure for CPU tensors.
- TensorData - Union type for tensor data on any device.
- SliceSpec - Slice specification for tensor indexing.
- TypeOptions - Options for type conversion
- SliceOptions - Options for slice operations
- SliceScatterOptions - Options for slice_scatter operations
- ToOptions - Options for to() operations
- AlphaBetaOptions - Options for operations with alpha and beta (addmm, addmv, etc.)
- ValueOptions - Options for operations with a value scaling factor (addcdiv, addcmul)
- ClampOptions - Options for clamp/clip operations
- TriangularOptions - Options for triangular operations (triu, tril) - simple diagonal offset only
- DiagflatOptions - Options for diagflat operation - simple offset only
- DiagonalOptions - Options for diagonal extraction operations (diagonal, diag) - with dimension support
- SqueezeOptions - Options for squeeze operations
- UnsqueezeOptions - Options for unsqueeze operations
- FlattenOptions - Options for flatten operations
- SizeOptions - Options for size operations
- StrideOptions - Options for stride operations
- ScatterReduceOptions - Options for scatter_reduce operations
- IndexPutOptions - Options for index_put operations
- PutOptions - Options for put operations
- TrapezoidOptions - Options for trapezoid operations
- SortOptions - Options for sort operations
- IscloseOptions - Options for isclose operations
- AllcloseOptions - Options for allclose operations
- TopkOptions - Options for topk operations
- KthvalueOptions - Options for kthvalue operations
- LogitOptions - Options for logit operations
- NanToNumOptions - Options for nan_to_num operations
- LogOptions - Options for log operations
- UniformOptions - Options for uniform_ operations
- RandomOptions - Options for random_ operations
- BernoulliOptions - Options for bernoulli operations
- ExponentialOptions - Options for exponential_ operations
- CauchyOptions - Options for cauchy_ operations
- LogNormalOptions - Options for log_normal_ operations
- GeometricOptions - Options for geometric_ operations
- LuSolveOptions - Options for lu_solve operations