/frameworks/ml/nn/runtime/test/specs/V1_2/ |
D | svdf_state_float16.mod.py | 25 weights_feature = Input("weights_feature", "TENSOR_FLOAT16", "{%d, %d}" % (units, input_size)) variable 34 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 38 weights_feature: [
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D | svdf_bias_present_float16.mod.py | 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT16", "{%d, %d}" % (features, input_size)) variable 36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 41 weights_feature: [
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D | svdf_float16.mod.py | 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT16", "{%d, %d}" % (features, input_size)) variable 36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 41 weights_feature: [
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/frameworks/ml/nn/runtime/test/specs/V1_0/ |
D | svdf_state.mod.py | 25 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size)) variable 34 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 38 weights_feature: [
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D | svdf.mod.py | 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) variable 36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 41 weights_feature: [
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D | svdf_bias_present.mod.py | 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) variable 36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 41 weights_feature: [
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D | svdf2.mod.py | 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) variable 36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 41 weights_feature: [
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/frameworks/ml/nn/runtime/test/specs/V1_1/ |
D | svdf_state_relaxed.mod.py | 25 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (units, input_size)) variable 34 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 39 weights_feature: [
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D | svdf2_relaxed.mod.py | 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) variable 36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 42 weights_feature: [
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D | svdf_relaxed.mod.py | 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) variable 36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 42 weights_feature: [
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D | svdf_bias_present_relaxed.mod.py | 27 weights_feature = Input("weights_feature", "TENSOR_FLOAT32", "{%d, %d}" % (features, input_size)) variable 36 model = model.Operation("SVDF", input, weights_feature, weights_time, bias, state_in, 42 weights_feature: [
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/frameworks/ml/nn/common/operations/ |
D | SVDF.cpp | 75 const RunTimeOperandInfo* weights_feature = in Prepare() local 84 const uint32_t num_filters = SizeOfDimension(weights_feature, 0); in Prepare() 88 NN_CHECK_EQ(SizeOfDimension(input, 1), SizeOfDimension(weights_feature, 1)); in Prepare()
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/frameworks/ml/nn/tools/api/ |
D | types.spec | 2272 * memory = push(conv1d(inputs, weights_feature, feature_dim, 2277 * * “weights_feature” is a weights matrix that processes the inputs (by 2304 * * 1: weights_feature.
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