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/third_party/mindspore/mindspore/ops/_grad/
Dgrad_implementations.py30 def bprop_max_and_minimum_grad_grad(x, y, z, out, dout): argument
32 out0 = F.cast(out[0] != 0, get_dtype(dout[0]))
33 out1 = F.cast(out[1] != 0, get_dtype(dout[1]))
34 dz = out0 * dout[0] + out1 * dout[1]
39 def bprop_relu_grad_grad(x, y, out, dout): argument
42 dy = input_grad(dout, y)
47 def bprop_scalar_add(x, y, out, dout): argument
49 return dout, dout
53 def bprop_scalar_mul(x, y, out, dout): argument
55 return dout*y, dout*x
[all …]
Dgrad_math_ops.py64 def _sum_grad(x, axis, dout): argument
69 grad = reshape(dout, output_shape_kept_dims)
73 def _min_or_max_grad(x, axis, out, dout): argument
78 grad = reshape(dout, output_shape_kept_dims)
85 def _argmin_or_argmax_grad(x, axis, keep_dims, op, out, dout): argument
96 dout_expand = dout[1]
99 dout_expand = expand(dout[1], onehot_axis)
120 def bprop(x, w, out, dout): argument
122 dx = mul1(w, dout)
124 dx = mul1(dout, w)
[all …]
Dgrad_array_ops.py50 def bprop(dtype, dims, x, out, dout): argument
60 def bprop(dims, dtype, out, dout): argument
70 def bprop(dims, dtype, out, dout): argument
80 def bprop(x, out, dout): argument
90 def dout_cast_tensor(dout, x): argument
94 dx = cast(dout, get_dtype(x))
99 def dout_cast_number(dout, x): argument
103 dx = cast(dout, get_dtype(x))
108 def dout_cast_row_tensor(dout, x): argument
112 values = cast(dout.values, get_dtype(x))
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Dgrad_comm_ops.py50 def bprop(x, out, dout): argument
51 dy1 = mul(dout, out)
58 def bprop(x, out, dout): argument
59 if F.issubclass_(F.typeof(dout), mstype.tensor):
60 dx = all_reduce_grad(dout)
62 indices = all_gather(dout.indices)
63 grad = all_gather(dout.values)
64 dx = RowTensor(indices, grad, dout.dense_shape)
68 def bprop(x, out, dout): argument
69 if F.issubclass_(F.typeof(dout), mstype.tensor):
[all …]
Dgrad_nn_ops.py38 def bprop(x, w, out, dout): argument
39 return dout, bias_grad(dout)
60 def bprop(x, w, out, dout): argument
67 dx = input_grad(dout, w, x_shape)
71 dw = filter_grad(dout, x, w_shape)
90 def bprop(x, w, out, dout): argument
91 dx = input_grad(w, dout, get_shape(x))
92 dw = filter_grad(x, dout, get_shape(w))
112 def bprop(x, w, out, dout): argument
113 dx = input_grad(dout, w)
[all …]
Dgrad_quant_ops.py31 def bprop(x, x_min, x_max, out, dout): argument
32 dx = op(dout, x, x_min, x_max)
44 def bprop(x, x_min, x_max, out, dout): argument
45 dx = op(dout, x, x_min, x_max)
57 def bprop(x, x_min, x_max, out, dout): argument
58 dx = op(dout, x, x_min, x_max)
73 def bprop(x, x_min, x_max, out, dout): argument
74 dx = op(dout, x, x_min, x_max)
85 def bprop(x, mean, variance, global_step, out, dout): argument
86 dx = op(dout[0], dout[1], x, out[0], out[1], global_step)
[all …]
Dgrad_inner_ops.py50 def bprop(x, y, out, dout): argument
51 shape = F.shape(dout)
52 dtype = get_dtype(dout)
54 dx = inner.MatrixDiagPart()(dout, assist)
65 def bprop(x, y, out, dout): argument
68 shape = F.shape(dout)
69 dtype = get_dtype(dout)
71 return inner.MatrixDiag()(dout, assist), zeros_like(y)
75 return inner.MatrixSetDiag()(zeros_like(x), dout, assist), zeros_like(y)
85 def bprop(x, y, z, out, dout): argument
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Dgrad_sparse.py27 def bprop_make_sparse_tensor(indices, values, dense_shape, out, dout): argument
29 return zeros_like(indices), F.sparse_tensor_get_values(dout), ()
33 def bprop_sparse_tensor_get_indices(sparse_tensor, out, dout): argument
39 def bprop_sparse_tensor_get_values(sparse_tensor, out, dout): argument
42 dout,
47 def bprop_sparse_tensor_get_dense_shape(sparse_tensor, out, dout): argument
56 def bprop(indices, values, dense_shape, out, dout): argument
57 return zeros_like(indices), F.gather_nd(dout, indices), zeros_like(dense_shape)
69 def bprop(indices, values, dense_shape, dense, out, dout): argument
70 dense_grad = sparse_tensor_dense_mat_mul(indices, values, dense_shape, dout)
[all …]
Dgrad_other_ops.py31 def bprop(x, y, out, dout): argument
32 return (dout, zeros_like(y))
40 def bprop(x, out, dout): argument
49 def bprop(x, y, out, dout): argument
59 def bprop(x, scale, b, mean, variance, out, dout): argument
62 out = input_grad(dout[0], x, scale, saved_mean, saved_variance)
74 def bprop(x, out, dout): argument
75 return (dout,)
Dgrad_debug_ops.py29 def bprop(tag, x, out, dout): argument
38 def bprop(tag, x, out, dout): argument
47 def bprop(tag, x, out, dout): argument
56 def bprop(tag, x, out, dout): argument
66 def bprop(x, out, dout): argument
67 return (f(dout),)
/third_party/mindspore/tests/st/ops/gpu/
Dtest_fake_quant_perchannel_grad.py32 def construct(self, dout, x, minq, maxq): argument
33 return self.op(dout, x, minq, maxq)
41 dout = np.random.uniform(-1, 1, size=[4]).astype('float32')
45 expect = dout
48 output = net(Tensor(dout), Tensor(x), Tensor(min_val), Tensor(max_val))
63 dout = np.random.uniform(-1, 1, size=[4]).astype('float32')
67 expect = np.array([0.0, dout[1], dout[2], 0.0]).astype(np.float32)
70 output = net(Tensor(dout), Tensor(x), Tensor(min_val), Tensor(max_val))
85 dout = np.random.uniform(-1, 1, size=[4]).astype('float32')
89 expect = np.array([0.0, dout[1], dout[2], 0.0]).astype(np.float32)
[all …]
Dtest_fake_quant_perlayer_grad.py31 def construct(self, dout, x, minq, maxq): argument
32 return self.op(dout, x, minq, maxq)
40 dout = np.random.uniform(-1, 1, size=[6]).astype('float32')
44 expect = np.array([0.0, dout[1], dout[2], dout[3], dout[4], 0.0]).astype(np.float32)
47 output = net(Tensor(dout), Tensor(x), Tensor(min_val), Tensor(max_val))
61 dout = np.random.uniform(-1, 1, size=[6]).astype('float32')
65 expect = np.array([0.0, dout[1], dout[2], dout[3], dout[4], 0.0]).astype(np.float32)
68 output = net(Tensor(dout), Tensor(x), Tensor(min_val), Tensor(max_val))
82 dout = np.random.uniform(-1, 1, size=[6]).astype('float32')
86 expect = np.array([0.0, dout[1], dout[2], dout[3], dout[4], 0.0]).astype(np.float32)
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/third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/
Dunary_op_grad_impl.cu20 __global__ void SqrtGradKernel(const T *input, const T *dout, T *output, const size_t count) { in SqrtGradKernel() argument
23 float dout_f = static_cast<float>(dout[i]); in SqrtGradKernel()
31 __global__ void RsqrtGradKernel(const T *input, const T *dout, T *output, const size_t count) { in RsqrtGradKernel() argument
34 float dout_f = static_cast<float>(dout[i]); in RsqrtGradKernel()
43 __global__ void AsinGradKernel(const T *input, const T *dout, T *output, const size_t count) { in AsinGradKernel() argument
47 output[i] = dout[i] / sqt; in AsinGradKernel()
53 __global__ void AsinGradKernel(const half *input, const half *dout, half *output, const size_t coun… in AsinGradKernel() argument
57 output[i] = dout[i] / sqt; in AsinGradKernel()
63 __global__ void ACosGradKernel(const T *input, const T *dout, T *output, const size_t count) { in ACosGradKernel() argument
68 output[i] = neg_one * dout[i] / sqt; in ACosGradKernel()
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Dunary_op_grad_impl.cuh22 void SqrtGrad(const T *input, const T *dout, T *output, const size_t count, cudaStream_t cuda_strea…
24 void RsqrtGrad(const T *input, const T *dout, T *output, const size_t count, cudaStream_t cuda_stre…
26 void AsinGrad(const T *input, const T *dout, T *output, const size_t count, cudaStream_t cuda_strea…
28 void ACosGrad(const T *input, const T *dout, T *output, const size_t count, cudaStream_t cuda_strea…
30 void AtanGrad(const T *input, const T *dout, T *output, const size_t count, cudaStream_t cuda_strea…
32 void AsinhGrad(const T *input, const T *dout, T *output, const size_t count, cudaStream_t cuda_stre…
34 void AcoshGrad(const T *input, const T *dout, T *output, const size_t count, cudaStream_t cuda_stre…
36 void ReciprocalGrad(const T *input, const T *dout, T *output, const size_t count, cudaStream_t cuda…
/third_party/mindspore/mindspore/ops/_grad_experimental/
Dgrad_array_ops.py33 def bprop(input_data, mask, value, out, dout): argument
35 dinput = mul_op(dout, (1 - mask))
36 dvalue = mul_op(dout, mask)
55 def bprop(x, indices, update, out, dout): argument
56 update_grad = neg(gather_nd(dout, indices))
57 return dout, zeros_like(indices), update_grad
62 def tensor_scatter_possible_replacement(x, indices, updates, out, dout): argument
74 dx = dout * F.cast(x_indicators, F.dtype(dout)) / F.cast(indicators, F.dtype(dout))
75 …dupdates = gather_nd(dout / F.cast(indicators, F.dtype(dout)), indices) * F.cast(out_indicators, F…
83 def bprop(x, indices, updates, out, dout): argument
[all …]
Dgrad_math_ops.py42 def bprop(input_x, input_y, out, dout): argument
43 dout_shape = F.shape(dout)
49 dout_transpose = transpose(dout, dout_perm)
51 dx = input_grad(dout, input_x, input_y, out)
65 def bprop(start, end, weight, out, dout): argument
66 dout = F.cast(dout, mstype.float32)
67 dstart = mul_op(dout, 1 - weight)
68 dend = mul_op(dout, weight)
69 dweight = mul_op(dout, sub_op(end, start))
92 def bprop(input_x, out, dout): argument
[all …]
Dgrad_nn_ops.py30 def bprop(log_probs, targets, input_lengths, target_lengths, out, dout): argument
31 … grad = ctc_loss_grad(dout[1], log_probs, targets, input_lengths, target_lengths, out[0], out[1])
43 def bprop(predict, label, out, dout): argument
44 dx = grad(predict, label, dout)
45 dy = grad(label, predict, dout)
56 def bprop(input_x, out, dout): argument
57 dx = input_grad(dout, input_x)
/third_party/mindspore/tests/vm_impl/
Dnn_ops_vm_impl.py133 def vm_impl(x, dout, argmax): argument
135 dout = dout.asnumpy()
137 dx = vm.max_pool_grad_with_argmax(x, dout, arg_max,
172 def vm_impl(x, out, dout): argument
174 dout = dout.asnumpy()
175 … out = vm.max_pool_grad(x, dout, self.kernel_size[-2], self.kernel_size[-1], self.strides[-2])
197 def vm_impl(dout, origin_shape): argument
198 dout = dout.asnumpy()
199 …out = vm.avg_pool_grad(dout, origin_shape, self.kernel_size[-2], self.kernel_size[-1], self.stride…
239 def vm_impl(dout, w, x_size): argument
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Dvm_me.py48 def avg_pool_grad(dout, origin_shape, pool_h, pool_w, stride): argument
63 _, _, height, width = dout.shape
121 def _batch_norm_grad(dout, x, scale, save_mean, save_inv_variance, \ argument
133 dx_norm = scale * dout
138 dgamma = np.sum(dout * x_norm, axis=0)
139 dbeta = np.sum(dout, axis=0)
284 def conv2d_backprop_filter(dout, x, w_size, stride=1, pad=0): argument
287 dout = dout.transpose(0, 2, 3, 1).reshape(-1, filter_num)
289 dw = np.dot(col.T, dout)
294 def conv2d_backprop_input(dout, x_size, weight, stride=1, pad=0): argument
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/third_party/mesa3d/src/amd/common/
Dac_surface_meta_address_test.c206 ADDR2_COMPUTE_DCCINFO_OUTPUT dout = {sizeof(dout)}; in one_dcc_address_test() local
211 dout.pMipInfo = meta_mip_info; in one_dcc_address_test()
226 int ret = Addr2ComputeDccInfo(addrlib, &din, &dout); in one_dcc_address_test()
249 in.compressBlkWidth = dout.compressBlkWidth; in one_dcc_address_test()
250 in.compressBlkHeight = dout.compressBlkHeight; in one_dcc_address_test()
251 in.compressBlkDepth = dout.compressBlkDepth; in one_dcc_address_test()
252 in.metaBlkWidth = dout.metaBlkWidth; in one_dcc_address_test()
253 in.metaBlkHeight = dout.metaBlkHeight; in one_dcc_address_test()
254 in.metaBlkDepth = dout.metaBlkDepth; in one_dcc_address_test()
255 in.dccRamSliceSize = dout.dccRamSliceSize; in one_dcc_address_test()
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/third_party/mindspore/tests/st/ops/cpu/
Dtest_bias_add_grad.py31 def construct(self, dout): argument
32 return self.bias_add_grad(dout)
39 dout = np.ones([2, 3]).astype(np.float32)
41 output = bias_add_grad(Tensor(dout))
51 dout = np.ones([2, 3, 4, 4]).astype(np.float32)
53 output = bias_add_grad(Tensor(dout))
62 dout = np.ones([2, 3, 4, 4, 2]).astype(np.float32)
64 output = bias_add_grad(Tensor(dout))
Dtest_l2normalize_grad_op.py31 def construct(self, input_x, output, dout): argument
32 return self.ops(input_x, output, dout)
43 dout = np.arange(24, 48).astype(np.float32).reshape((2, 3, 4))
45 except_asn = (dout - output * np.sum(output * dout, axis=axis, keepdims=True)
49 dout = Tensor(dout, mstype.float32)
50 net_output = net(input_x, output, dout).asnumpy()
/third_party/mindspore/tests/st/ops/graph_kernel/
Dtest_bias_add_grad.py29 def construct(self, dout): argument
30 return self.bias_add_grad(dout)
33 def get_output(dout, enable_graph_kernel=False): argument
36 output = opt(Tensor(dout))
41 dout = np.random.normal(0, 1, shape).astype(dtype)
43 expect = get_output(dout, False)
44 output = get_output(dout, True)
Dtest_sqrt_grad.py28 def construct(self, x, dout): argument
29 return self.sqrt_grad(x, dout)
32 def get_output(x, dout, enable_graph_kernel=False): argument
35 output = net(x, dout)
41 dout = Tensor(np.random.normal(0, 1, shape_dout).astype(dtype))
43 expect = get_output(x, dout, False)
44 output = get_output(x, dout, True)
/third_party/mindspore/mindspore/nn/layer/
Dthor_layer.py144 def save_gradient(self, dout): argument
149 out = dout
152 shape = self.shape(dout)
154 matrix_g = self.cube_matmul(dout, dout)
158 dout_shape = self.shape(dout)
160 matrix_g = self.cube_matmul(dout, dout)
445 def save_gradient(self, dout): argument
447 out = dout
449 dout_shape = self.shape(dout)
450 dout = self.transpose(dout, (0, 2, 3, 1))
[all …]

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