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Fix node names ending with _fwd not being able to find weights #795

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Fix node names ending with _fwd not being able to find weights #795

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36 changes: 27 additions & 9 deletions mmdnn/conversion/mxnet/mxnet_parser.py
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Original file line number Diff line number Diff line change
Expand Up @@ -402,10 +402,14 @@ def rename_FullyConnected(self, source_node):

# weights
if self.weight_loaded:
if source_node.name.endswith("_fwd"):
node_prefix = source_node.name[:-4]
else:
node_prefix = source_node.name
if self.data_format == 'NM':
self.set_weight(source_node.name, "weights", self.weight_data.get(source_node.name + "_weight").asnumpy().transpose((1, 0)))
self.set_weight(source_node.name, "weights", self.weight_data.get(node_prefix + "_weight").asnumpy().transpose((1, 0)))
else:
weight = self.weight_data.get(source_node.name + "_weight").asnumpy().transpose((1, 0))
weight = self.weight_data.get(node_prefix + "_weight").asnumpy().transpose((1, 0))
original_shape = weight.shape

channel_first_list = self.trace_shape(source_node, IR_node)
Expand All @@ -417,7 +421,7 @@ def rename_FullyConnected(self, source_node):
self.set_weight(source_node.name, "weights", weight)

if IR_node.attr["use_bias"].b:
self.set_weight(source_node.name, "bias", self.weight_data.get(source_node.name + "_bias").asnumpy())
self.set_weight(source_node.name, "bias", self.weight_data.get(node_prefix + "_bias").asnumpy())

if not self.data_format == 'NM':
# print("Warning: Layer [{}] has changed model data format from [{}] to [NM]".format(source_node.name, self.data_format))
Expand Down Expand Up @@ -502,15 +506,19 @@ def rename_Convolution(self, source_node):

# weights
if self.weight_loaded:
weight = self.weight_data.get(source_node.name + "_weight").asnumpy()
if source_node.name.endswith("_fwd"):
node_prefix = source_node.name[:-4]
else:
node_prefix = source_node.name
weight = self.weight_data.get(node_prefix + "_weight").asnumpy()
if not layout in MXNetParser.channels_last:
weight = MXNetParser.transpose(weight, dim)
if IR_node.op == "DepthwiseConv":
weight = weight.transpose(0, 1, 3, 2)
self.set_weight(source_node.name, "weights", weight)

if IR_node.attr["use_bias"].b:
self.set_weight(source_node.name, "bias", self.weight_data.get(source_node.name + "_bias").asnumpy())
self.set_weight(source_node.name, "bias", self.weight_data.get(node_prefix + "_bias").asnumpy())


def rename_Activation(self, source_node):
Expand All @@ -537,19 +545,29 @@ def rename_BatchNorm(self, source_node):

# weights
if self.weight_loaded:
if source_node.name.endswith("_fwd"):
node_prefix = source_node.name[:-4]
else:
node_prefix = source_node.name
# gamma
if IR_node.attr["scale"].b:
self.set_weight(source_node.name, "scale", self.weight_data.get(source_node.name + "_gamma").asnumpy())
self.set_weight(source_node.name, "scale", self.weight_data.get(node_prefix + "_gamma").asnumpy())

# beta
if IR_node.attr["bias"].b:
self.set_weight(source_node.name, "bias", self.weight_data.get(source_node.name + "_beta").asnumpy())
self.set_weight(source_node.name, "bias", self.weight_data.get(node_prefix + "_beta").asnumpy())

# mean
self.set_weight(source_node.name, "mean", self.weight_data.get(source_node.name + "_moving_mean").asnumpy())
try:
self.set_weight(source_node.name, "mean", self.weight_data.get(node_prefix + "_moving_mean").asnumpy())
except AttributeError:
self.set_weight(source_node.name, "mean", self.weight_data.get(node_prefix + "_running_mean").asnumpy())

# var
self.set_weight(source_node.name, "var", self.weight_data.get(source_node.name + "_moving_var").asnumpy())
try:
self.set_weight(source_node.name, "var", self.weight_data.get(node_prefix + "_moving_var").asnumpy())
except AttributeError:
self.set_weight(source_node.name, "var", self.weight_data.get(node_prefix + "_running_var").asnumpy())


def rename_Pooling(self, source_node):
Expand Down