/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/ |
D | pad_quant8_signed.mod.py | 20 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [1, 2, variable 26 model = Model().Operation("PAD", input0, paddings).To(output0) 48 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1]) variable 51 model = Model().Operation("PAD", input0, paddings).To(output0) 61 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable 67 model = Model().Operation("PAD", input0, paddings).To(output0) 84 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable 90 model = Model().Operation("PAD", input0, paddings).To(output0) 104 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable 111 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0) [all …]
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D | space_to_batch_quant8_signed.mod.py | 20 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) variable 23 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output) 50 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) variable 53 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output) 78 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 1, 2, 4]) variable 81 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output) 110 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) variable 113 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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/packages/modules/NeuralNetworks/runtime/test/specs/AIDL_V3/ |
D | mirror_pad.mod.py | 35 paddings = orig_paddings.copy() 40 if paddings[padding_index] == input_dims[i]: 41 paddings[padding_index] = input_dims[i] - 1 44 padding_tensor = Parameter("padding", ("TENSOR_INT32", [len(input_dims), 2]), paddings) 45 output_dims = [sum(x) for x in zip(input_dims, paddings[0::2], paddings[1::2])] 52 numpy_paddings = list(zip(paddings[0::2], paddings[1::2]))
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D | mirror_pad_tensorflow.mod.py | 20 def test(name, input_dims, input_values, paddings, mode, output_dims, output_values): argument 22 paddings = Parameter("paddings", ("TENSOR_INT32", [len(input_dims), 2]), paddings) 25 model = Model().Operation("MIRROR_PAD", t, paddings, mode).To(output)
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/packages/modules/NeuralNetworks/common/cpu_operations/ |
D | Reshape.cpp | 91 bool padGeneric(const T* inputData, const Shape& inputShape, const int32_t* paddings, T padValue, in padGeneric() argument 105 leftPaddings.push_back(paddings[i * 2]); in padGeneric() 106 rightPaddings.push_back(paddings[i * 2 + 1]); in padGeneric() 191 const int32_t* paddings, float padValue, float* outputData, 194 const int32_t* paddings, _Float16 padValue, _Float16* outputData, 197 const int32_t* paddings, uint8_t padValue, uint8_t* outputData, 200 const int32_t* paddings, int8_t padValue, int8_t* outputData,
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/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/ |
D | pad_quant8_nonzero.mod.py | 21 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable 27 model = Model().Operation("PAD", input0, paddings).To(output0)
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D | pad_quant8.mod.py | 18 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable 24 model = Model().IntroducedIn("V1_1").Operation("PAD", input0, paddings).To(output0)
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D | pad_low_rank_quant8.mod.py | 18 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1]) variable 21 model = Model().IntroducedIn("V1_1").Operation("PAD", input0, paddings).To(output0)
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D | pad_v2_1_quant8.mod.py | 18 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable 25 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
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D | pad_low_rank.mod.py | 18 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1]) variable 21 model = Model().Operation("PAD", input0, paddings).To(output0)
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D | pad_v2_low_rank_quant8.mod.py | 18 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1]) variable 22 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
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D | pad_v2_low_rank.mod.py | 18 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1]) variable 22 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
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D | pad_v2_1_float.mod.py | 18 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable 25 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
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D | space_to_batch_quant8_nonzero.mod.py | 23 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) variable 26 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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D | pad_v2_all_dims_quant8.mod.py | 20 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [1, 2, variable 27 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
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D | pad_v2_all_dims.mod.py | 20 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [1, 2, variable 27 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
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/packages/modules/NeuralNetworks/runtime/test/specs/V1_1/ |
D | space_to_batch_float_1.mod.py | 4 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) variable 7 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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D | space_to_batch_quant8_1.mod.py | 4 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) variable 7 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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D | space_to_batch_quant8_3.mod.py | 4 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 1, 2, 4]) variable 7 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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D | space_to_batch_float_3.mod.py | 4 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 1, 2, 4]) variable 7 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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D | space_to_batch.mod.py | 4 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) variable 7 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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D | space_to_batch_quant8_2.mod.py | 4 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) variable 7 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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D | space_to_batch_float_2.mod.py | 4 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) variable 7 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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D | space_to_batch_float_2_relaxed.mod.py | 20 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) variable 23 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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D | space_to_batch_relaxed.mod.py | 20 paddings = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) variable 23 model = model.Operation("SPACE_TO_BATCH_ND", i1, block, paddings).To(output)
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