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/packages/modules/NeuralNetworks/runtime/test/specs/V1_3/
Dpad_quant8_signed.mod.py20 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 …]
Dspace_to_batch_quant8_signed.mod.py20 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)
/packages/modules/NeuralNetworks/runtime/test/specs/AIDL_V3/
Dmirror_pad.mod.py35 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]))
Dmirror_pad_tensorflow.mod.py20 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)
/packages/modules/NeuralNetworks/common/cpu_operations/
DReshape.cpp91 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,
/packages/modules/NeuralNetworks/runtime/test/specs/V1_2/
Dpad_quant8_nonzero.mod.py21 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable
27 model = Model().Operation("PAD", input0, paddings).To(output0)
Dpad_quant8.mod.py18 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable
24 model = Model().IntroducedIn("V1_1").Operation("PAD", input0, paddings).To(output0)
Dpad_low_rank_quant8.mod.py18 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1]) variable
21 model = Model().IntroducedIn("V1_1").Operation("PAD", input0, paddings).To(output0)
Dpad_v2_1_quant8.mod.py18 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable
25 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
Dpad_low_rank.mod.py18 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1]) variable
21 model = Model().Operation("PAD", input0, paddings).To(output0)
Dpad_v2_low_rank_quant8.mod.py18 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1]) variable
22 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
Dpad_v2_low_rank.mod.py18 paddings = Parameter("paddings", "TENSOR_INT32", "{1, 2}", [3, 1]) variable
22 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
Dpad_v2_1_float.mod.py18 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [0, 0, variable
25 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
Dspace_to_batch_quant8_nonzero.mod.py23 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)
Dpad_v2_all_dims_quant8.mod.py20 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [1, 2, variable
27 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
Dpad_v2_all_dims.mod.py20 paddings = Parameter("paddings", "TENSOR_INT32", "{4, 2}", [1, 2, variable
27 model = Model().Operation("PAD_V2", input0, paddings, pad_value).To(output0)
/packages/modules/NeuralNetworks/runtime/test/specs/V1_1/
Dspace_to_batch_float_1.mod.py4 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)
Dspace_to_batch_quant8_1.mod.py4 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)
Dspace_to_batch_quant8_3.mod.py4 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)
Dspace_to_batch_float_3.mod.py4 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)
Dspace_to_batch.mod.py4 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)
Dspace_to_batch_quant8_2.mod.py4 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)
Dspace_to_batch_float_2.mod.py4 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)
Dspace_to_batch_float_2_relaxed.mod.py20 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)
Dspace_to_batch_relaxed.mod.py20 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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