| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/cpu/ |
| D | dynamic_assign_cpu_kernel.cc | 65 auto input_x_shape = AnfAlgo::GetPrevNodeOutputInferShape(node, 0); in LaunchKernel() local
68 for (size_t i = 0; i < input_x_shape.size(); ++i) { in LaunchKernel()
69 batch_size_ *= input_x_shape[i]; in LaunchKernel()
72 if (input_x_shape.size() != input_y_shape.size()) { in LaunchKernel()
75 for (size_t i = 0; i < input_x_shape.size(); ++i) { in LaunchKernel()
76 if (input_x_shape[i] != input_y_shape[i]) { in LaunchKernel()
100 …(void)std::transform(input_x_shape.begin(), input_x_shape.end(), std::back_inserter(shape_tmp), Si… in LaunchKernel()
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| D | assign_cpu_kernel.cc | 41 auto input_x_shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0); in InitKernel() local
43 if (input_x_shape.size() != input_y_shape.size()) { in InitKernel()
46 for (size_t i = 0; i < input_x_shape.size(); ++i) { in InitKernel()
47 if (input_x_shape[i] != input_y_shape[i]) { in InitKernel()
50 batch_size_ *= input_x_shape[i]; in InitKernel()
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| D | map_uniform_cpu_kernel.cc | 58 auto input_x_shape = AnfAlgo::GetPrevNodeOutputInferShape(node, 0); in LaunchKernel() local
60 for (size_t i = 0; i < input_x_shape.size(); ++i) { in LaunchKernel()
61 batch_size_ *= input_x_shape[i]; in LaunchKernel()
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| D | l2normalize_grad_cpu_kernel.cc | 79 auto input_x_shape = input_shape_list_[0]; in CheckInputShape() local
80 if (input_x_shape.size() != 0) { in CheckInputShape()
81 if (std::any_of(input_x_shape.begin(), input_x_shape.end(), [](size_t i) { return i == 0; })) { in CheckInputShape()
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| /third_party/mindspore/mindspore/ops/_op_impl/_custom_op/ |
| D | fused_abs_max1_impl.py | 76 def shape0(tik_instance, input_x_shape, input_x, res): argument
79 for val in input_x_shape:
100 def shape1(tik_instance, input_x_shape, ori_shape, input_x, res): argument
123 for val in input_x_shape:
146 def shape2(tik_instance, input_x_shape, input_x, res): argument
149 for val in input_x_shape:
242 def shape3(tik_instance, input_x_shape, ori_shape, input_x, res): argument
250 for val in input_x_shape:
275 def shape4(tik_instance, input_x_shape, input_x, res): argument
278 for val in input_x_shape:
[all …]
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| D | matrix_combine_impl.py | 36 input_x_shape = input_x.get("shape")
44 input_x = tik_instance.Tensor("float32", input_x_shape, name="input_x", scope=tik.scope_gm)
48 matrix_dim = input_x_shape[0] * input_x_shape[1]
49 if input_x_shape[0] == 1 and input_x_shape[1] == 64:
62 tik_instance.for_range(0, input_x_shape[0]) as i:
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| D | transpose02314_impl.py | 42 def _error_feedback(input_x_shape): argument
56 if input_x_shape not in support_shape:
57 raise RuntimeError("input_shape %s is not supported" % str(input_x_shape))
63 input_x_shape = input_x.get("shape")
65 input_x_shape = tuple(input_x_shape)
67 _error_feedback(input_x_shape)
71 input_x = tik_instance.Tensor("float16", input_x_shape, name="input_x", scope=tik.scope_gm)
75 if tuple(input_x_shape) == (32, 4, 112, 112, 16):
77 elif tuple(input_x_shape) == (32, 4, 56, 56, 16):
79 elif tuple(input_x_shape) == (32, 16, 56, 56, 16):
[all …]
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| D | cholesky_trsm_impl.py | 36 input_x_shape = input_x.get("shape")
39 matrix_dim = input_x_shape[0]
50 input_x = tik_instance.Tensor("float32", input_x_shape, name="input_x", scope=tik.scope_gm)
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| D | img2col_impl.py | 820 input_x_shape = input_x.get("shape")
822 n_shape, c1_shape, h_shape, w_shape, c0_shape = input_x_shape
829 input_shape = (tuple(input_x_shape), input_x_dtype, (filter_h, filter_w), (stride_h, stride_w))
860 input_x = tik_instance.Tensor("float16", input_x_shape, name="input_x", scope=tik.scope_gm)
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| /third_party/mindspore/mindspore/core/ops/ |
| D | reduce.cc | 36 std::vector<int64_t> infer_shape_reduce(std::vector<int64_t> input_x_shape, const ValuePtr axis_val… in infer_shape_reduce() argument
38 int64_t dim = SizeToLong(input_x_shape.size()); in infer_shape_reduce()
63 (void)out_shape.emplace_back(input_x_shape[LongToSize(i)]); in infer_shape_reduce()
73 …auto input_x_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[0]->BuildShape())[… in InferShape() local
76 auto out_shape = infer_shape_reduce(input_x_shape, axis_value, keep_dims); in InferShape()
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| /third_party/mindspore/mindspore/ops/operations/ |
| D | _embedding_cache_ops.py | 50 def check_shape(self, input_x_shape, indices_shape, update_shape, max_num_shape): argument
95 def check_shape(self, input_x_shape, max_num_shape, offset_shape): argument
302 def check_shape(self, input_x_shape, cum_sum_arr_shape, shift_idx_shape): argument
303 return input_x_shape
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| D | array_ops.py | 3824 def infer_shape(self, input_x_shape, indices_shape, updates_shape): argument
3829 if indices_shape[-1] > len(input_x_shape):
3835 updates_shape_check = indices_shape[:-1] + input_x_shape[indices_shape[-1]:]
3843 return input_x_shape
3909 def infer_shape(self, input_x_shape, indices_shape, updates_shape): argument
3914 if indices_shape[-1] > len(input_x_shape):
3920 updates_shape_check = indices_shape[:-1] + input_x_shape[indices_shape[-1]:]
3928 return input_x_shape
6236 def infer_shape(self, input_x_shape, indices_shape, updates_shape): argument
6241 if indices_shape[-1] > len(input_x_shape):
[all …]
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| D | _quant_ops.py | 226 def infer_shape(self, input_x_shape, alpha_shape, quant_max_shape): argument
227 validator.check_int(len(input_x_shape), 1, Rel.GE, "input_x rank", self.name)
230 return input_x_shape
383 def infer_shape(self, input_x_shape, alpha_shape, quant_max_shape): argument
384 if self.is_ascend and len(input_x_shape) not in self.ascend_support_x_rank:
387 validator.check_int(len(input_x_shape), 1, Rel.GE, "input_x rank", self.name)
388 if len(input_x_shape) == 1:
391 …validator.check_equal_int(alpha_shape[0], input_x_shape[self.channel_axis], "alpha rank", self.nam…
393 return input_x_shape
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| D | nn_ops.py | 3861 def infer_shape(self, input_x_shape, weight_shape): argument
3862 input_x_dim = len(input_x_shape)
3869 channel_num = input_x_shape[1]
3877 return input_x_shape
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| /third_party/mindspore/mindspore/core/ops/grad/ |
| D | soft_shrink_grad.cc | 39 …auto input_x_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[1]->BuildShape())[… in SoftShrinkGradInferShape() local
41 …ils::Check("input_grad_shape", input_grad_shape, kEqual, "input_x_shape", input_x_shape, prim_name, in SoftShrinkGradInferShape()
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| D | hsigmoid_grad.cc | 43 …auto input_x_shape = CheckAndConvertUtils::ConvertShapePtrToShapeMap(input_args[1]->BuildShape())[… in InferShape() local
44 …CheckAndConvertUtils::Check("grads_shape", grads_shape, kEqual, "input_x_shape", input_x_shape, pr… in InferShape()
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| /third_party/mindspore/mindspore/ccsrc/backend/kernel_compiler/tbe/ |
| D | tbe_adapter.cc | 260 auto input_x_shape = AnfAlgo::GetOutputInferShape(anf_node, 0); in GenTopKV2IndicesTensorInfo() local
261 size_t last_dim = input_x_shape[input_x_shape.size() - 1]; in GenTopKV2IndicesTensorInfo()
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| /third_party/mindspore/mindspore/ccsrc/transform/express_ir/ |
| D | onnx_exporter.cc | 1069 auto input_x_shape = dyn_cast<abstract::Shape>(node->input(kOneNum)->Shape()); in ExportPrimBatchMatMul() local
1079 for (size_t i = 0; i < input_x_shape->shape().size() - kTwoNum; i++) { in ExportPrimBatchMatMul()
1082 attr_proto->add_ints(SizeToLong(input_x_shape->shape().size()) - IntToLong(kOneNum)); in ExportPrimBatchMatMul()
1083 attr_proto->add_ints(SizeToLong(input_x_shape->shape().size()) - IntToLong(kTwoNum)); in ExportPrimBatchMatMul()
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