#!/usr/bin/env python3
# SPDX-License-Identifier: LGPL-3.0-or-later
from tensorflow.python.framework import (
ops,
)
from deepmd.tf.env import (
op_module,
tf,
)
@ops.RegisterGradient("MatmulFlt2fixNvnmd")
[docs]
def _MatmulFlt2fixNvnmdGrad(op, grad):
x = op.inputs[0]
w = op.inputs[1]
# transpose for 2-dimension and 3-dimension multiplication
if len(x.shape) == 3:
x_T = tf.transpose(x, [0, 2, 1])
w_T = tf.transpose(w, [0, 2, 1])
else:
x_T = tf.transpose(x)
w_T = tf.transpose(w)
# calcualte
# dx = tf.matmul(grad, w_T)
# dw = tf.matmul(x_T, grad)
dx = op_module.matmul_flt_nvnmd(grad, w_T, 1, 1)
dw = op_module.matmul_flt_nvnmd(x_T, grad, 1, 1)
# add shape for output of matmul_nvnmd
shx = x.shape.as_list()
shw = w.shape.as_list()
shx = [None if (d == -1) else d for d in shx]
shw = [None if (d == -1) else d for d in shw]
dx = tf.ensure_shape(dx, shx)
dw = tf.ensure_shape(dw, shw)
return [dx, dw]