tf.raw_ops.BatchMatMulV3

Multiplies slices of two tensors in batches.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.raw_ops.BatchMatMulV3

tf.raw_ops.BatchMatMulV3(
    x, y, Tout, adj_x=False, adj_y=False, name=None
)

Multiplies all slices of Tensor x 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:

r_o = c_x if adj_x else r_x
c_o = r_y if adj_y else c_y

It is computed as:

output[..., :, :] = matrix(x[..., :, :]) * matrix(y[..., :, :])

Note: BatchMatMulV3 supports broadcasting in the batch dimensions. More about broadcasting here.

Args
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].
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.
name	A name for the operation (optional).

Returns
A Tensor of type Tout.