problem with converting model used ResNet50 from h5 to pb in keras(Keras) Can't reload a trained resnet50 model from a h5 fileHow do tf.gradients() work?Keras Multi GPU example gives ResourceExhaustedErrorTensorflow converting keras model for tensorflowjsTensorFlow InvalidArgumentError/Value error occurs with small change of codeTensorflow - 'Unable to get element as bytes' errorAttributeError: 'Sequential' object has no attribute 'output_names'Convert trained Tensorflow model to a TensorFlow.JS model (Inception trained model)Predicting and Training in different threads Keras TensorflowAttributeError: 'Sequential' object has no attribute 'output_names'. Not toco problem
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problem with converting model used ResNet50 from h5 to pb in keras
(Keras) Can't reload a trained resnet50 model from a h5 fileHow do tf.gradients() work?Keras Multi GPU example gives ResourceExhaustedErrorTensorflow converting keras model for tensorflowjsTensorFlow InvalidArgumentError/Value error occurs with small change of codeTensorflow - 'Unable to get element as bytes' errorAttributeError: 'Sequential' object has no attribute 'output_names'Convert trained Tensorflow model to a TensorFlow.JS model (Inception trained model)Predicting and Training in different threads Keras TensorflowAttributeError: 'Sequential' object has no attribute 'output_names'. Not toco problem
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0
I'm new to Neural Networks, and I'm familiar with keras only. I'm trying to create a model that works on Android. I have created a model that is .h5, so i need to convert it to .pb in order to run it on Android. I have a code to convert it, but the code didn't work as expected.
First of all, I have created many models using Keras that were built from scratch and I was doing some experiments with these models. The conversion code works perfectly fine with the previous models
After that, I tried to create a model using pre-trained model (ResNet50) with existing weights, you can find the pre-trained model here.
This model works obviously better because it wasn't built from scratch, but I couldn't convert it at all with the same convert code that I have.
This is the convert code I used:
import tensorflow as tf
from keras import backend as K
from keras.models import model_from_json, model_from_yaml
from tensorflow.python.tools import optimize_for_inference_lib,
freeze_graph
import keras.backend.tensorflow_backend as Q
-------------------------------------------------------------------------
model = tf.keras.models.load_model('great_model.h5')
model_name = 'model_70'
-------------------------------------------------------------------------
def export_model(saver, model, input_node_names, output_node_name):
tf.train.write_graph(K.get_session().graph_def, 'out',
model_name + '_graph.pbtxt')
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
freeze_graph.freeze_graph('out/' + model_name + '_graph.pbtxt', None,
False, 'out/' + model_name + '.chkp', output_node_name,
"save/restore_all", "save/Const:0",
'out/frozen_' + model_name + '.pb', True, "")
input_graph_def = tf.GraphDef()
with tf.gfile.Open('out/frozen_' + model_name + '.pb', "rb") as f:
input_graph_def.ParseFromString(f.read())
output_graph_def = optimize_for_inference_lib.optimize_for_inference(
input_graph_def, input_node_names, [output_node_name],
tf.float32.as_datatype_enum)
with tf.gfile.FastGFile('out/opt_' + model_name + '.pb', "wb") as f:
f.write(output_graph_def.SerializeToString())
print("graph saved!")
--------------------------------------------------------------------------
export_model(tf.train.Saver() ,model ,["conv2d_1_input"]
,"dense_2/Softmax")
Note: i got the Convert code from this GitHub.
As you might notice here:
model = tf.keras.models.load_model('great_model.h5')
I loaded the model using tensorflow included keras instead of using independent keras package, because thanks to this Stack Overflow question, I found out that when you want to load a model that has a pre-trained model in it, you shouldn't load it using an independent keras package, but use the tensorflow included keras one.
As for the error I mentioned before, here it is, a massive one:
WARNING:tensorflow:Error in loading the saved optimizer state. As a
result, your model is starting with a freshly initialized optimizer.
Traceback (most recent call last):
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1334, in _do_call
return fn(*args)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1407, in
_call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error
while reading resource variable conv1/bias from Container: localhost. This could mean that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp = ReadVariableOp[_class=
["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 37, in
<module>
export_model(tf.train.Saver() ,model ,["conv2d_1_input"]
,"dense_2/Softmax")
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 17, in
export_model
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingsaver.py", line 1458, in save
raise exc
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingsaver.py", line 1441, in save
self.saver_def.filename_tensor_name: checkpoint_file)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 929, in run
run_metadata_ptr)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1328, in _do_run
run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error
while reading resource variable conv1/bias from Container: localhost. This could mean that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp (defined at
C:/Users/User/PycharmProjects/tensorflow/convert.py:12) =
ReadVariableOp[_class=["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
Caused by op 'conv1/bias/Read/ReadVariableOp', defined at:
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 12, in
<module>
model = tf.keras.models.load_model('great_model.h5')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesaving.py", line 230, in
load_model
model = model_from_config(model_config, custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesaving.py", line 310, in
model_from_config
return deserialize(config, custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersserialization.py", line 64, in
deserializeprintable_module_name='layer')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasutilsgeneric_utils.py", line 173, in
deserialize_keras_object list(custom_objects.items())))
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesequential.py", line 339, in
from_config custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersserialization.py", line 64, in
deserialize printable_module_name='layer')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasutilsgeneric_utils.py", line 173, in
deserialize_keras_object list(custom_objects.items())))
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginenetwork.py", line 1302, in
from_config process_node(layer, node_data)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginenetwork.py", line 1260, in
process_node layer(input_tensors[0], **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 746, in
__call__
self.build(input_shapes)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersconvolutional.py", line 174, in
build dtype=self.dtype)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 609, in
add_weight aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingcheckpointablebase.py", line 639, in
_add_variable_with_custom_getter
**kwargs_for_getter)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 1977, in
make_variable aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 183, in __call__
return cls._variable_v1_call(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 146, in
_variable_v1_call aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 125, in <lambda>
previous_getter = lambda **kwargs: default_variable_creator(None,
**kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariable_scope.py", line 2437, in
default_variable_creator
import_scope=import_scope)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 187, in __call__
return super(VariableMetaclass, cls).__call__(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 297, in
__init__
constraint=constraint)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 449, in
_init_from_args
value = self._read_variable_op()
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 727, in
_read_variable_op
self._dtype)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsgen_resource_variable_ops.py", line 563, in read_variable_op
"ReadVariableOp", resource=resource, dtype=dtype, name=name)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkop_def_library.py", line 787, in
_apply_op_helper
op_def=op_def)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonutildeprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkops.py", line 3274, in create_op
op_def=op_def)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkops.py", line 1770, in __init__
self._traceback = tf_stack.extract_stack()
FailedPreconditionError (see above for traceback): Error while reading
resource variable conv1/bias from Container: localhost. This could mean
that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp (defined at
C:/Users/User/PycharmProjects/tensorflow/convert.py:12) =
ReadVariableOp[_class=["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
The problem starts in this line in convert code:
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
I think the solution has something to do with using functions with tesnorflow.keras instead of keras., but I don't know how to do it. I looked everywhere, but I couldn't find anything useful.
Is it possible to convert a model that has ResNet50 in it from .h5 to .pb?
python tensorflow keras deep-learning resnet
edited Mar 22 at 22:05
karel
2,35392832
asked Mar 22 at 21:18
CayldenCaylden
12
add a comment |
0
I'm new to Neural Networks, and I'm familiar with keras only. I'm trying to create a model that works on Android. I have created a model that is .h5, so i need to convert it to .pb in order to run it on Android. I have a code to convert it, but the code didn't work as expected.
First of all, I have created many models using Keras that were built from scratch and I was doing some experiments with these models. The conversion code works perfectly fine with the previous models
After that, I tried to create a model using pre-trained model (ResNet50) with existing weights, you can find the pre-trained model here.
This model works obviously better because it wasn't built from scratch, but I couldn't convert it at all with the same convert code that I have.
This is the convert code I used:
import tensorflow as tf
from keras import backend as K
from keras.models import model_from_json, model_from_yaml
from tensorflow.python.tools import optimize_for_inference_lib,
freeze_graph
import keras.backend.tensorflow_backend as Q
-------------------------------------------------------------------------
model = tf.keras.models.load_model('great_model.h5')
model_name = 'model_70'
-------------------------------------------------------------------------
def export_model(saver, model, input_node_names, output_node_name):
tf.train.write_graph(K.get_session().graph_def, 'out',
model_name + '_graph.pbtxt')
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
freeze_graph.freeze_graph('out/' + model_name + '_graph.pbtxt', None,
False, 'out/' + model_name + '.chkp', output_node_name,
"save/restore_all", "save/Const:0",
'out/frozen_' + model_name + '.pb', True, "")
input_graph_def = tf.GraphDef()
with tf.gfile.Open('out/frozen_' + model_name + '.pb', "rb") as f:
input_graph_def.ParseFromString(f.read())
output_graph_def = optimize_for_inference_lib.optimize_for_inference(
input_graph_def, input_node_names, [output_node_name],
tf.float32.as_datatype_enum)
with tf.gfile.FastGFile('out/opt_' + model_name + '.pb', "wb") as f:
f.write(output_graph_def.SerializeToString())
print("graph saved!")
--------------------------------------------------------------------------
export_model(tf.train.Saver() ,model ,["conv2d_1_input"]
,"dense_2/Softmax")
Note: i got the Convert code from this GitHub.
As you might notice here:
model = tf.keras.models.load_model('great_model.h5')
I loaded the model using tensorflow included keras instead of using independent keras package, because thanks to this Stack Overflow question, I found out that when you want to load a model that has a pre-trained model in it, you shouldn't load it using an independent keras package, but use the tensorflow included keras one.
As for the error I mentioned before, here it is, a massive one:
WARNING:tensorflow:Error in loading the saved optimizer state. As a
result, your model is starting with a freshly initialized optimizer.
Traceback (most recent call last):
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1334, in _do_call
return fn(*args)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1407, in
_call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error
while reading resource variable conv1/bias from Container: localhost. This could mean that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp = ReadVariableOp[_class=
["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 37, in
<module>
export_model(tf.train.Saver() ,model ,["conv2d_1_input"]
,"dense_2/Softmax")
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 17, in
export_model
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingsaver.py", line 1458, in save
raise exc
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingsaver.py", line 1441, in save
self.saver_def.filename_tensor_name: checkpoint_file)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 929, in run
run_metadata_ptr)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1328, in _do_run
run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error
while reading resource variable conv1/bias from Container: localhost. This could mean that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp (defined at
C:/Users/User/PycharmProjects/tensorflow/convert.py:12) =
ReadVariableOp[_class=["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
Caused by op 'conv1/bias/Read/ReadVariableOp', defined at:
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 12, in
<module>
model = tf.keras.models.load_model('great_model.h5')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesaving.py", line 230, in
load_model
model = model_from_config(model_config, custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesaving.py", line 310, in
model_from_config
return deserialize(config, custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersserialization.py", line 64, in
deserializeprintable_module_name='layer')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasutilsgeneric_utils.py", line 173, in
deserialize_keras_object list(custom_objects.items())))
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesequential.py", line 339, in
from_config custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersserialization.py", line 64, in
deserialize printable_module_name='layer')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasutilsgeneric_utils.py", line 173, in
deserialize_keras_object list(custom_objects.items())))
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginenetwork.py", line 1302, in
from_config process_node(layer, node_data)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginenetwork.py", line 1260, in
process_node layer(input_tensors[0], **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 746, in
__call__
self.build(input_shapes)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersconvolutional.py", line 174, in
build dtype=self.dtype)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 609, in
add_weight aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingcheckpointablebase.py", line 639, in
_add_variable_with_custom_getter
**kwargs_for_getter)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 1977, in
make_variable aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 183, in __call__
return cls._variable_v1_call(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 146, in
_variable_v1_call aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 125, in <lambda>
previous_getter = lambda **kwargs: default_variable_creator(None,
**kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariable_scope.py", line 2437, in
default_variable_creator
import_scope=import_scope)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 187, in __call__
return super(VariableMetaclass, cls).__call__(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 297, in
__init__
constraint=constraint)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 449, in
_init_from_args
value = self._read_variable_op()
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 727, in
_read_variable_op
self._dtype)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsgen_resource_variable_ops.py", line 563, in read_variable_op
"ReadVariableOp", resource=resource, dtype=dtype, name=name)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkop_def_library.py", line 787, in
_apply_op_helper
op_def=op_def)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonutildeprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkops.py", line 3274, in create_op
op_def=op_def)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkops.py", line 1770, in __init__
self._traceback = tf_stack.extract_stack()
FailedPreconditionError (see above for traceback): Error while reading
resource variable conv1/bias from Container: localhost. This could mean
that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp (defined at
C:/Users/User/PycharmProjects/tensorflow/convert.py:12) =
ReadVariableOp[_class=["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
The problem starts in this line in convert code:
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
I think the solution has something to do with using functions with tesnorflow.keras instead of keras., but I don't know how to do it. I looked everywhere, but I couldn't find anything useful.
Is it possible to convert a model that has ResNet50 in it from .h5 to .pb?
python tensorflow keras deep-learning resnet
edited Mar 22 at 22:05
karel
2,35392832
asked Mar 22 at 21:18
CayldenCaylden
12
add a comment |
0
0
0
I'm new to Neural Networks, and I'm familiar with keras only. I'm trying to create a model that works on Android. I have created a model that is .h5, so i need to convert it to .pb in order to run it on Android. I have a code to convert it, but the code didn't work as expected.
First of all, I have created many models using Keras that were built from scratch and I was doing some experiments with these models. The conversion code works perfectly fine with the previous models
After that, I tried to create a model using pre-trained model (ResNet50) with existing weights, you can find the pre-trained model here.
This model works obviously better because it wasn't built from scratch, but I couldn't convert it at all with the same convert code that I have.
This is the convert code I used:
import tensorflow as tf
from keras import backend as K
from keras.models import model_from_json, model_from_yaml
from tensorflow.python.tools import optimize_for_inference_lib,
freeze_graph
import keras.backend.tensorflow_backend as Q
-------------------------------------------------------------------------
model = tf.keras.models.load_model('great_model.h5')
model_name = 'model_70'
-------------------------------------------------------------------------
def export_model(saver, model, input_node_names, output_node_name):
tf.train.write_graph(K.get_session().graph_def, 'out',
model_name + '_graph.pbtxt')
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
freeze_graph.freeze_graph('out/' + model_name + '_graph.pbtxt', None,
False, 'out/' + model_name + '.chkp', output_node_name,
"save/restore_all", "save/Const:0",
'out/frozen_' + model_name + '.pb', True, "")
input_graph_def = tf.GraphDef()
with tf.gfile.Open('out/frozen_' + model_name + '.pb', "rb") as f:
input_graph_def.ParseFromString(f.read())
output_graph_def = optimize_for_inference_lib.optimize_for_inference(
input_graph_def, input_node_names, [output_node_name],
tf.float32.as_datatype_enum)
with tf.gfile.FastGFile('out/opt_' + model_name + '.pb', "wb") as f:
f.write(output_graph_def.SerializeToString())
print("graph saved!")
--------------------------------------------------------------------------
export_model(tf.train.Saver() ,model ,["conv2d_1_input"]
,"dense_2/Softmax")
Note: i got the Convert code from this GitHub.
As you might notice here:
model = tf.keras.models.load_model('great_model.h5')
I loaded the model using tensorflow included keras instead of using independent keras package, because thanks to this Stack Overflow question, I found out that when you want to load a model that has a pre-trained model in it, you shouldn't load it using an independent keras package, but use the tensorflow included keras one.
As for the error I mentioned before, here it is, a massive one:
WARNING:tensorflow:Error in loading the saved optimizer state. As a
result, your model is starting with a freshly initialized optimizer.
Traceback (most recent call last):
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1334, in _do_call
return fn(*args)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1407, in
_call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error
while reading resource variable conv1/bias from Container: localhost. This could mean that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp = ReadVariableOp[_class=
["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 37, in
<module>
export_model(tf.train.Saver() ,model ,["conv2d_1_input"]
,"dense_2/Softmax")
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 17, in
export_model
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingsaver.py", line 1458, in save
raise exc
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingsaver.py", line 1441, in save
self.saver_def.filename_tensor_name: checkpoint_file)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 929, in run
run_metadata_ptr)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1328, in _do_run
run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error
while reading resource variable conv1/bias from Container: localhost. This could mean that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp (defined at
C:/Users/User/PycharmProjects/tensorflow/convert.py:12) =
ReadVariableOp[_class=["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
Caused by op 'conv1/bias/Read/ReadVariableOp', defined at:
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 12, in
<module>
model = tf.keras.models.load_model('great_model.h5')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesaving.py", line 230, in
load_model
model = model_from_config(model_config, custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesaving.py", line 310, in
model_from_config
return deserialize(config, custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersserialization.py", line 64, in
deserializeprintable_module_name='layer')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasutilsgeneric_utils.py", line 173, in
deserialize_keras_object list(custom_objects.items())))
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesequential.py", line 339, in
from_config custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersserialization.py", line 64, in
deserialize printable_module_name='layer')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasutilsgeneric_utils.py", line 173, in
deserialize_keras_object list(custom_objects.items())))
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginenetwork.py", line 1302, in
from_config process_node(layer, node_data)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginenetwork.py", line 1260, in
process_node layer(input_tensors[0], **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 746, in
__call__
self.build(input_shapes)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersconvolutional.py", line 174, in
build dtype=self.dtype)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 609, in
add_weight aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingcheckpointablebase.py", line 639, in
_add_variable_with_custom_getter
**kwargs_for_getter)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 1977, in
make_variable aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 183, in __call__
return cls._variable_v1_call(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 146, in
_variable_v1_call aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 125, in <lambda>
previous_getter = lambda **kwargs: default_variable_creator(None,
**kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariable_scope.py", line 2437, in
default_variable_creator
import_scope=import_scope)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 187, in __call__
return super(VariableMetaclass, cls).__call__(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 297, in
__init__
constraint=constraint)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 449, in
_init_from_args
value = self._read_variable_op()
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 727, in
_read_variable_op
self._dtype)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsgen_resource_variable_ops.py", line 563, in read_variable_op
"ReadVariableOp", resource=resource, dtype=dtype, name=name)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkop_def_library.py", line 787, in
_apply_op_helper
op_def=op_def)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonutildeprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkops.py", line 3274, in create_op
op_def=op_def)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkops.py", line 1770, in __init__
self._traceback = tf_stack.extract_stack()
FailedPreconditionError (see above for traceback): Error while reading
resource variable conv1/bias from Container: localhost. This could mean
that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp (defined at
C:/Users/User/PycharmProjects/tensorflow/convert.py:12) =
ReadVariableOp[_class=["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
The problem starts in this line in convert code:
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
I think the solution has something to do with using functions with tesnorflow.keras instead of keras., but I don't know how to do it. I looked everywhere, but I couldn't find anything useful.
Is it possible to convert a model that has ResNet50 in it from .h5 to .pb?
python tensorflow keras deep-learning resnet
edited Mar 22 at 22:05
karel
2,35392832
asked Mar 22 at 21:18
CayldenCaylden
12
I'm new to Neural Networks, and I'm familiar with keras only. I'm trying to create a model that works on Android. I have created a model that is .h5, so i need to convert it to .pb in order to run it on Android. I have a code to convert it, but the code didn't work as expected.
First of all, I have created many models using Keras that were built from scratch and I was doing some experiments with these models. The conversion code works perfectly fine with the previous models
After that, I tried to create a model using pre-trained model (ResNet50) with existing weights, you can find the pre-trained model here.
This model works obviously better because it wasn't built from scratch, but I couldn't convert it at all with the same convert code that I have.
This is the convert code I used:
import tensorflow as tf
from keras import backend as K
from keras.models import model_from_json, model_from_yaml
from tensorflow.python.tools import optimize_for_inference_lib,
freeze_graph
import keras.backend.tensorflow_backend as Q
-------------------------------------------------------------------------
model = tf.keras.models.load_model('great_model.h5')
model_name = 'model_70'
-------------------------------------------------------------------------
def export_model(saver, model, input_node_names, output_node_name):
tf.train.write_graph(K.get_session().graph_def, 'out',
model_name + '_graph.pbtxt')
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
freeze_graph.freeze_graph('out/' + model_name + '_graph.pbtxt', None,
False, 'out/' + model_name + '.chkp', output_node_name,
"save/restore_all", "save/Const:0",
'out/frozen_' + model_name + '.pb', True, "")
input_graph_def = tf.GraphDef()
with tf.gfile.Open('out/frozen_' + model_name + '.pb', "rb") as f:
input_graph_def.ParseFromString(f.read())
output_graph_def = optimize_for_inference_lib.optimize_for_inference(
input_graph_def, input_node_names, [output_node_name],
tf.float32.as_datatype_enum)
with tf.gfile.FastGFile('out/opt_' + model_name + '.pb', "wb") as f:
f.write(output_graph_def.SerializeToString())
print("graph saved!")
--------------------------------------------------------------------------
export_model(tf.train.Saver() ,model ,["conv2d_1_input"]
,"dense_2/Softmax")
Note: i got the Convert code from this GitHub.
As you might notice here:
model = tf.keras.models.load_model('great_model.h5')
I loaded the model using tensorflow included keras instead of using independent keras package, because thanks to this Stack Overflow question, I found out that when you want to load a model that has a pre-trained model in it, you shouldn't load it using an independent keras package, but use the tensorflow included keras one.
As for the error I mentioned before, here it is, a massive one:
WARNING:tensorflow:Error in loading the saved optimizer state. As a
result, your model is starting with a freshly initialized optimizer.
Traceback (most recent call last):
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1334, in _do_call
return fn(*args)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1407, in
_call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error
while reading resource variable conv1/bias from Container: localhost. This could mean that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp = ReadVariableOp[_class=
["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 37, in
<module>
export_model(tf.train.Saver() ,model ,["conv2d_1_input"]
,"dense_2/Softmax")
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 17, in
export_model
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingsaver.py", line 1458, in save
raise exc
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingsaver.py", line 1441, in save
self.saver_def.filename_tensor_name: checkpoint_file)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 929, in run
run_metadata_ptr)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1328, in _do_run
run_metadata)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonclientsession.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.FailedPreconditionError: Error
while reading resource variable conv1/bias from Container: localhost. This could mean that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp (defined at
C:/Users/User/PycharmProjects/tensorflow/convert.py:12) =
ReadVariableOp[_class=["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
Caused by op 'conv1/bias/Read/ReadVariableOp', defined at:
File "C:/Users/User/PycharmProjects/tensorflow/convert.py", line 12, in
<module>
model = tf.keras.models.load_model('great_model.h5')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesaving.py", line 230, in
load_model
model = model_from_config(model_config, custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesaving.py", line 310, in
model_from_config
return deserialize(config, custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersserialization.py", line 64, in
deserializeprintable_module_name='layer')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasutilsgeneric_utils.py", line 173, in
deserialize_keras_object list(custom_objects.items())))
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginesequential.py", line 339, in
from_config custom_objects=custom_objects)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersserialization.py", line 64, in
deserialize printable_module_name='layer')
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasutilsgeneric_utils.py", line 173, in
deserialize_keras_object list(custom_objects.items())))
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginenetwork.py", line 1302, in
from_config process_node(layer, node_data)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginenetwork.py", line 1260, in
process_node layer(input_tensors[0], **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 746, in
__call__
self.build(input_shapes)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkeraslayersconvolutional.py", line 174, in
build dtype=self.dtype)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 609, in
add_weight aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythontrainingcheckpointablebase.py", line 639, in
_add_variable_with_custom_getter
**kwargs_for_getter)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonkerasenginebase_layer.py", line 1977, in
make_variable aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 183, in __call__
return cls._variable_v1_call(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 146, in
_variable_v1_call aggregation=aggregation)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 125, in <lambda>
previous_getter = lambda **kwargs: default_variable_creator(None,
**kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariable_scope.py", line 2437, in
default_variable_creator
import_scope=import_scope)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsvariables.py", line 187, in __call__
return super(VariableMetaclass, cls).__call__(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 297, in
__init__
constraint=constraint)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 449, in
_init_from_args
value = self._read_variable_op()
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsresource_variable_ops.py", line 727, in
_read_variable_op
self._dtype)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonopsgen_resource_variable_ops.py", line 563, in read_variable_op
"ReadVariableOp", resource=resource, dtype=dtype, name=name)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkop_def_library.py", line 787, in
_apply_op_helper
op_def=op_def)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonutildeprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkops.py", line 3274, in create_op
op_def=op_def)
File "C:UsersUserAppDataLocalProgramsPythonPython36libsite-
packagestensorflowpythonframeworkops.py", line 1770, in __init__
self._traceback = tf_stack.extract_stack()
FailedPreconditionError (see above for traceback): Error while reading
resource variable conv1/bias from Container: localhost. This could mean
that the variable was uninitialized. Not found: Resource
localhost/conv1/bias/class tensorflow::Var does not exist.
[[node conv1/bias/Read/ReadVariableOp (defined at
C:/Users/User/PycharmProjects/tensorflow/convert.py:12) =
ReadVariableOp[_class=["loc:@conv1/bias"], dtype=DT_FLOAT,
_device="/job:localhost/replica:0/task:0/device:CPU:0"](conv1/bias)]]
The problem starts in this line in convert code:
saver.save(K.get_session(), 'out/' + model_name + '.chkp')
I think the solution has something to do with using functions with tesnorflow.keras instead of keras., but I don't know how to do it. I looked everywhere, but I couldn't find anything useful.
Is it possible to convert a model that has ResNet50 in it from .h5 to .pb?
python tensorflow keras deep-learning resnet
python tensorflow keras deep-learning resnet
edited Mar 22 at 22:05
karel
2,35392832
asked Mar 22 at 21:18
CayldenCaylden
12
edited Mar 22 at 22:05
karel
2,35392832
asked Mar 22 at 21:18
CayldenCaylden
12
edited Mar 22 at 22:05
karel
2,35392832
edited Mar 22 at 22:05
karel
2,35392832
edited Mar 22 at 22:05
karel
2,35392832
2,35392832
asked Mar 22 at 21:18
CayldenCaylden
12
asked Mar 22 at 21:18
CayldenCaylden
12
asked Mar 22 at 21:18
CayldenCaylden
12
12
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