Variables
	X = helper.make_tensor_value_info('X', TensorProto.FLOAT, [1, 1, 32, 32])

	W_info = helper.make_tensor_value_info('W', TensorProto.FLOAT, [5, 1, 3, 3])

	W = np.array([[[[-1,-1,-1],[-1,8.1,-1],[-1,-1,-1]]],[[[0,-1,0],[-1,5,-1],[0,-1,0]]],[[[-2,-1,0],[-1,1,1],[0,1,2]]],[[[1,2,1],[0,0,0],[-1,-2,-1]]],[[[1,0,-1],[2,0,-2],[1,0,-1]]]]).astype(np.float32)

	Y = helper.make_tensor_value_info('Y', TensorProto.FLOAT, [1, 5, 32, 32])

	conv1

	graph_def

	model_def = helper.make_model(graph_def, producer_name='benchmarks')

Variable Documentation

◆ conv1

e2_onnx_build.conv1

Initial value:

 =  helper.make_node(
         'Conv',         # name
         ['X', 'W'],     # inputs
         ['Y'],          # outputs
         
         kernel_shape=[3, 3],
         strides=[1, 1],
         pads=[1, 1, 1, 1],
         )

Definition at line 19 of file e2_onnx_build.py.

◆ graph_def

e2_onnx_build.graph_def

Initial value:

 =  helper.make_graph(
         nodes=[conv1],     # graph nodes
         name= 'conv_model',   # graph name
         inputs =      [X, W_info],  # graph inputs
         outputs =     [Y],          # graph outputs
         initializer = [W],
         )

Definition at line 30 of file e2_onnx_build.py.

◆ model_def

e2_onnx_build.model_def = helper.make_model(graph_def, producer_name='benchmarks')

Definition at line 38 of file e2_onnx_build.py.

◆ W

e2_onnx_build.W = np.array([[[[-1,-1,-1],[-1,8.1,-1],[-1,-1,-1]]],[[[0,-1,0],[-1,5,-1],[0,-1,0]]],[[[-2,-1,0],[-1,1,1],[0,1,2]]],[[[1,2,1],[0,0,0],[-1,-2,-1]]],[[[1,0,-1],[2,0,-2],[1,0,-1]]]]).astype(np.float32)

Definition at line 12 of file e2_onnx_build.py.