tf.linalg.solve
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Solves systems of linear equations.
tf.linalg.solve(
matrix: Annotated[Any, TV_MatrixSolve_T],
rhs: Annotated[Any, TV_MatrixSolve_T],
adjoint: bool = False,
name=None
) -> Annotated[Any, TV_MatrixSolve_T]
Used in the notebooks
| Used in the guide |
Used in the tutorials |
|
|
|
Matrix is a tensor of shape [..., M, M] whose inner-most 2 dimensions
form square matrices. Rhs is a tensor of shape [..., M, K]. The output is
a tensor shape [..., M, K]. If adjoint is False then each output matrix
satisfies matrix[..., :, :] * output[..., :, :] = rhs[..., :, :].
If adjoint is True then each output matrix satisfies
adjoint(matrix[..., :, :]) * output[..., :, :] = rhs[..., :, :].
Args |
|---|
matrix
|
A Tensor. Must be one of the following types: float64, float32, half, complex64, complex128.
Shape is [..., M, M].
|
rhs
|
A Tensor. Must have the same type as matrix.
Shape is [..., M, K].
|
adjoint
|
An optional bool. Defaults to False.
Boolean indicating whether to solve with matrix or its (block-wise)
adjoint.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor. Has the same type as matrix.
|
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.linalg.solve\n\n\u003cbr /\u003e\n\nSolves systems of linear equations.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.linalg.solve`](https://www.tensorflow.org/api_docs/python/tf/linalg/solve), [`tf.compat.v1.matrix_solve`](https://www.tensorflow.org/api_docs/python/tf/linalg/solve)\n\n\u003cbr /\u003e\n\n tf.linalg.solve(\n matrix: Annotated[Any, TV_MatrixSolve_T],\n rhs: Annotated[Any, TV_MatrixSolve_T],\n adjoint: bool = False,\n name=None\n ) -\u003e Annotated[Any, TV_MatrixSolve_T]\n\n### Used in the notebooks\n\n| Used in the guide | Used in the tutorials |\n|--------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|\n| - [Advanced automatic differentiation](https://www.tensorflow.org/guide/advanced_autodiff) | - [A Tour of TensorFlow Probability](https://www.tensorflow.org/probability/examples/A_Tour_of_TensorFlow_Probability) |\n\n`Matrix` is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions\nform square matrices. `Rhs` is a tensor of shape `[..., M, K]`. The `output` is\na tensor shape `[..., M, K]`. If `adjoint` is `False` then each output matrix\nsatisfies `matrix[..., :, :] * output[..., :, :] = rhs[..., :, :]`.\nIf `adjoint` is `True` then each output matrix satisfies\n`adjoint(matrix[..., :, :]) * output[..., :, :] = rhs[..., :, :]`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------|----------------------------------------------------------------------------------------------------------------------------------|\n| `matrix` | A `Tensor`. Must be one of the following types: `float64`, `float32`, `half`, `complex64`, `complex128`. Shape is `[..., M, M]`. |\n| `rhs` | A `Tensor`. Must have the same type as `matrix`. Shape is `[..., M, K]`. |\n| `adjoint` | An optional `bool`. Defaults to `False`. Boolean indicating whether to solve with `matrix` or its (block-wise) adjoint. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Tensor`. Has the same type as `matrix`. ||\n\n\u003cbr /\u003e"]]
