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| e1_onnx_build.X = helper.make_tensor_value_info('X', TensorProto.FLOAT, [1,784]) |
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| e1_onnx_build.W_info = helper.make_tensor_value_info('W', TensorProto.FLOAT, [784,10]) |
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| e1_onnx_build.W = np.random.randn(784,10).astype(np.float32) |
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| e1_onnx_build.B_info = helper.make_tensor_value_info('B', TensorProto.FLOAT, [1,10]) |
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| e1_onnx_build.B = np.ones([1,10]).astype(np.float32) |
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| e1_onnx_build.Z = helper.make_tensor_value_info('Z', TensorProto.FLOAT, [1,10]) |
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| e1_onnx_build.matmul |
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| e1_onnx_build.bias |
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| e1_onnx_build.softmax |
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| e1_onnx_build.graph_def |
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| e1_onnx_build.model_def = helper.make_model(graph_def, producer_name='benchmarks') |
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