spazewalker · August 17, 2021 08:00 · spazewalker · Jun 23, 2021
diff --git a/convert_jasper_to_FP32.py b/convert_jasper_to_FP32.py
 import onnx

 # Load base onnx model
 model = onnx.load("./jasper-onnx/1/model.onnx")

 # Change input data type FLOAT16 ==> FLOAT
 inp = model.graph.input[0]
 model.graph.input.remove(inp)
 inp.type.tensor_type.elem_type = 1
 model.graph.input.insert(0,inp)

 # Change output data type FLOAT16 ==> FLOAT
 out = model.graph.output[0]
 model.graph.output.remove(out)
 out.type.tensor_type.elem_type = 1
 model.graph.output.insert(0,out)

 # Change data type FLOAT16 ==> FLOAT of every initilizer
 for i,init in enumerate(model.graph.initializer):
    model.graph.initializer.remove(init)
    init.data_type = 1
    init.raw_data = np.frombuffer(init.raw_data, count=np.product(init.dims), dtype=np.float16).astype(np.float32).tobytes()
    model.graph.initializer.insert(i,init)
    
 # This part adds an additional reshape node to handle the inconsistant input
 # from python and c++ of openCV. see https://github.com/opencv/opencv/issues/19091
 # 1. Make & insert a new node with 'Reshape' operation & required initializer
 tensor = numpy_helper.from_array(np.array([0,64,-1]),name='shape_reshape')
 model.graph.initializer.insert(0,tensor)
 node = onnx.helper.make_node(op_type='Reshape',inputs=['input__0','shape_reshape'], outputs=['input_reshaped'], name='reshape__0')
 model.graph.node.insert(0,node)
 # 2. Fix connection on next node
 model.graph.node[1].input[0] = 'input_reshaped'

 # Save FP32 model
 with open('jasper_dynamic_input_float.onnx','wb') as f:
    onnx.save_model(model,f)
	import onnx

	# Load base onnx model
	model = onnx.load("./jasper-onnx/1/model.onnx")

	# Change input data type FLOAT16 ==> FLOAT
	inp = model.graph.input[0]
	model.graph.input.remove(inp)
	inp.type.tensor_type.elem_type = 1
	model.graph.input.insert(0,inp)

	# Change output data type FLOAT16 ==> FLOAT
	out = model.graph.output[0]
	model.graph.output.remove(out)
	out.type.tensor_type.elem_type = 1
	model.graph.output.insert(0,out)

	# Change data type FLOAT16 ==> FLOAT of every initilizer
	for i,init in enumerate(model.graph.initializer):
	model.graph.initializer.remove(init)
	init.data_type = 1
	init.raw_data = np.frombuffer(init.raw_data, count=np.product(init.dims), dtype=np.float16).astype(np.float32).tobytes()
	model.graph.initializer.insert(i,init)

	# This part adds an additional reshape node to handle the inconsistant input
	# from python and c++ of openCV. see https://github.com/opencv/opencv/issues/19091
	# 1. Make & insert a new node with 'Reshape' operation & required initializer
	tensor = numpy_helper.from_array(np.array([0,64,-1]),name='shape_reshape')
	model.graph.initializer.insert(0,tensor)
	node = onnx.helper.make_node(op_type='Reshape',inputs=['input__0','shape_reshape'], outputs=['input_reshaped'], name='reshape__0')
	model.graph.node.insert(0,node)
	# 2. Fix connection on next node
	model.graph.node[1].input[0] = 'input_reshaped'

	# Save FP32 model
	with open('jasper_dynamic_input_float.onnx','wb') as f:
	onnx.save_model(model,f)