def emit_Reshape(self, IR_node):
raise NotImplementedError
shape_str = IRGraph.shapeToStr(IR_node.IR_layer.attr["shape"].shape, True)
self.add_body(1, "{:<15} = Reshape(name = \"{}\", target_shape = ({}))({})".format(
IR_node.variable_name,
IR_node.name,
shape_str,
self.IR_graph.get_node(IR_node.in_edges[0]).real_variable_name))
def emit_DataInput(self, IR_node):
shape_str = IRGraph.shapeToStr(IR_node.IR_layer.attr["shape"].shape)
dtype_str = ", dtype = '{}'".format(self.dtype_map[IR_node.layer.attr['dtype'].type]) if 'dtype' in IR_node.layer.attr else ""
self.add_body(1, "{:<15} = layers.Input(name = '{}', shape = ({},) {})".format(
IR_node.variable_name,
IR_node.name,
shape_str,
dtype_str))
def emit_DataInput(self, IR_node):
shape_str = IRGraph.shapeToStr(IR_node.IR_layer.attr["shape"].shape)
dtype_str = ", dtype = '{}'".format(self.dtype_map[IR_node.layer.attr['dtype'].type]) if 'dtype' in IR_node.layer.attr else ""
self.add_body(1, "{:<15} = layers.Input(name = '{}', shape = ({},) {})".format(
IR_node.variable_name,
IR_node.name,
shape_str,
dtype_str))
def emit_Reshape(self, IR_node):
def ShapetrToTuple(string, batch_none=False):
if batch_none == True:
ls = [int(item) for item in string.split(', ')]
ls.insert(0, None)
return tuple(ls)
else:
ls = [int(item) for item in string.split(', ')]
return tuple(ls)
last_node = self.IR_graph.get_node(IR_node.in_edges[0]).layer
input_shape_dims = last_node.attr["_output_shapes"].list.shape
target_shape_dims = IR_node.IR_layer.attr["_output_shapes"].list.shape
input_shape = ShapetrToTuple(IRGraph.shapeToStr(input_shape_dims[0]),
True)
target_shape = ShapetrToTuple(IRGraph.shapeToStr(target_shape_dims[0]))
def get_coreml_target_shape(target_shape):
if len(target_shape) == 1: #(D,)
coreml_shape = (1, target_shape[0], 1, 1)
elif len(target_shape) == 2: #(S,D)
coreml_shape = target_shape + (1, 1)
elif len(target_shape) == 3: #(H,W,C)
coreml_shape = (1, target_shape[2], target_shape[0],
target_shape[1])
else:
coreml_shape = None
return coreml_shape
def get_mode(input_shape, target_shape):
in_shape = input_shape[1:]
if len(in_shape) == 3 or len(target_shape) == 3:
return 1
else:
return 0
input_name = self.IR_graph.get_node(IR_node.in_edges[0]).real_name
new_shape = get_coreml_target_shape(target_shape)
mode = get_mode(input_shape, target_shape)
self.builder.add_reshape(name=IR_node.real_name,
input_name=input_name,
output_name=IR_node.real_name,
target_shape=new_shape,
mode=mode)
def emit_Reshape(self, IR_node):
assert False
shape_str = IRGraph.shapeToStr(IR_node.IR_layer.attr["shape"].shape,
True)
code = "{:<15} = Reshape(name = \"{}\", target_shape = ({}))({})".format(
IR_node.replace_scope(IR_node.name), IR_node.name, shape_str,
IR_node.replace_scope(IR_node.in_edges[0]))
return code
def emit_Reshape(self, IR_node):
def ShapetrToTuple(string, batch_none = False):
if batch_none == True:
ls = [int(item) for item in string.split(', ')]
ls.insert(0,None)
return tuple(ls)
else:
ls = [int(item) for item in string.split(', ')]
return tuple(ls)
last_node = self.IR_graph.get_node(IR_node.in_edges[0]).layer
input_shape_dims = last_node.attr["_output_shapes"].list.shape
target_shape_dims = IR_node.IR_layer.attr["_output_shapes"].list.shape
input_shape = ShapetrToTuple(IRGraph.shapeToStr(input_shape_dims[0]),True)
target_shape = ShapetrToTuple(IRGraph.shapeToStr(target_shape_dims[0]))
# print("input_shape, target_shape",input_shape,target_shape)
def get_coreml_target_shape(target_shape):
if len(target_shape) == 1: #(D,)
coreml_shape = (1,target_shape[0],1,1)
elif len(target_shape) == 2: #(S,D)
coreml_shape = target_shape + (1,1)
elif len(target_shape) == 3: #(H,W,C)
coreml_shape = (1, target_shape[2], target_shape[0], target_shape[1])
else:
coreml_shape = None
return coreml_shape
def get_mode(input_shape, target_shape):
in_shape = input_shape[1:]
if len(in_shape) == 3 or len(target_shape) == 3:
return 1
else:
return 0
new_shape = get_coreml_target_shape(target_shape)
mode = get_mode(input_shape, target_shape)
self.builder.add_reshape(
name=IR_node.real_name,
input_name=self.parent_variable_name(IR_node),
output_name=IR_node.real_name,
target_shape=new_shape,
mode=mode)
def emit_Reshape(self, IR_node):
shape_str = IRGraph.shapeToStr(IR_node.IR_layer.attr["shape"].shape,
True)
self.add_body(
1,
"{:<15} = Reshape(name = \"{}\", target_shape = ({}))({})".format(
IR_node.variable_name, IR_node.name, shape_str,
self.IR_graph.get_node(
IR_node.in_edges[0]).real_variable_name))
def _process_output_layers(self):
for name in self.IR_graph.output_layers:
IR_node = self.IR_graph.get_node(name)
shape_str = IRGraph.shapeToStr(
IR_node.layer.attr["_output_shapes"].list.shape[0])
if IR_node.layer.attr['dtype'].type == graph_pb2.DT_UNDEFINED:
IR_node.layer.attr['dtype'].type = graph_pb2.DT_FLOAT32
dtype_str = self.dtype_map[IR_node.layer.attr['dtype'].type]
self.add_body(
1, "{:<15} = helper.make_tensor_value_info('{}', {}, ({},))".
format(IR_node.variable_name + '_out', IR_node.variable_name,
dtype_str, shape_str))
self.outputs.append(IR_node.variable_name + '_out')
