Multiplies all slices of Tensorx and y (each slice can be
viewed as an element of a batch), and arranges the individual results
in a single output tensor of the same batch size. Each of the
individual slices can optionally be adjointed (to adjoint a matrix
means to transpose and conjugate it) before multiplication by setting
the adj_x or adj_y flag to True, which are by default False.
The input tensors x and y are 2-D or higher with shape [..., r_x, c_x]
and [..., r_y, c_y].
The output tensor is 2-D or higher with shape [..., r_o, c_o], where:
A Tensor. Must be one of the following types: bfloat16, half, float32, float64, uint8, int8, int16, int32, int64, complex64, complex128.
2-D or higher with shape [..., r_x, c_x].
y
A Tensor. Must be one of the following types: bfloat16, half, float32, float64, uint8, int8, int16, int32, int64, complex64, complex128.
2-D or higher with shape [..., r_y, c_y].
Tout
A tf.DType from: tf.bfloat16, tf.half, tf.float32, tf.float64, tf.int16, tf.int32, tf.int64, tf.complex64, tf.complex128.
If not spcified, Tout is the same type to input type.
adj_x
An optional bool. Defaults to False.
If True, adjoint the slices of x. Defaults to False.
adj_y
An optional bool. Defaults to False.
If True, adjoint the slices of y. Defaults to False.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.raw_ops.BatchMatMulV3\n\n\u003cbr /\u003e\n\nMultiplies slices of two tensors in batches.\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.raw_ops.BatchMatMulV3`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/BatchMatMulV3)\n\n\u003cbr /\u003e\n\n tf.raw_ops.BatchMatMulV3(\n x, y, Tout, adj_x=False, adj_y=False, name=None\n )\n\nMultiplies all slices of `Tensor` `x` and `y` (each slice can be\nviewed as an element of a batch), and arranges the individual results\nin a single output tensor of the same batch size. Each of the\nindividual slices can optionally be adjointed (to adjoint a matrix\nmeans to transpose and conjugate it) before multiplication by setting\nthe `adj_x` or `adj_y` flag to `True`, which are by default `False`.\n\nThe input tensors `x` and `y` are 2-D or higher with shape `[..., r_x, c_x]`\nand `[..., r_y, c_y]`.\n\nThe output tensor is 2-D or higher with shape `[..., r_o, c_o]`, where: \n\n r_o = c_x if adj_x else r_x\n c_o = r_y if adj_y else c_y\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| It is computed as ----------------- ||\n|---|---|\n| output\\[..., :, :\\] = matrix(x\\[..., :, :\\]) \\* matrix(y\\[..., :, :\\]) ||\n\n\u003cbr /\u003e\n\n| **Note:** `BatchMatMulV3` supports broadcasting in the batch dimensions. More about broadcasting [here](http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html).\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|---------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `x` | A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`, `complex128`. 2-D or higher with shape `[..., r_x, c_x]`. |\n| `y` | A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`, `uint8`, `int8`, `int16`, `int32`, `int64`, `complex64`, `complex128`. 2-D or higher with shape `[..., r_y, c_y]`. |\n| `Tout` | A [`tf.DType`](../../tf/dtypes/DType) from: `tf.bfloat16, tf.half, tf.float32, tf.float64, tf.int16, tf.int32, tf.int64, tf.complex64, tf.complex128`. If not spcified, Tout is the same type to input type. |\n| `adj_x` | An optional `bool`. Defaults to `False`. If `True`, adjoint the slices of `x`. Defaults to `False`. |\n| `adj_y` | An optional `bool`. Defaults to `False`. If `True`, adjoint the slices of `y`. Defaults to `False`. |\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` of type `Tout`. ||\n\n\u003cbr /\u003e"]]
