def print_tensors_in_checkpoint_file(file_name, tensor_name):
"""Prints tensors in a checkpoint file.
If no `tensor_name` is provided, prints the tensor names and shapes
in the checkpoint file.
If `tensor_name` is provided, prints the content of the tensor.
Args:
file_name: Name of the checkpoint file.
tensor_name: Name of the tensor in the checkpoint file to print.
"""
try:
if not tensor_name:
variables = checkpoints.list_variables(file_name)
for name, shape in variables:
print("%s\t%s" % (name, str(shape)))
else:
print("tensor_name: ", tensor_name)
print(checkpoints.load_variable(file_name, tensor_name))
except Exception as e: # pylint: disable=broad-except
print(str(e))
if "corrupted compressed block contents" in str(e):
print("It's likely that your checkpoint file has been compressed "
"with SNAPPY.")
def get_variable_names(self):
"""Returns list of all variable names in this model.
Returns:
List of names.
"""
return [name for name, _ in checkpoints.list_variables(self.model_dir)]
def testGetAllVariables(self):
checkpoint_dir = self.get_temp_dir()
with self.test_session() as session:
_create_checkpoints(session, checkpoint_dir)
self.assertEqual(checkpoints.list_variables(checkpoint_dir),
[("useful_scope/var4", [9, 9]), ("var1", [1, 10]),
("var2", [10, 10]), ("var3", [100, 100])])
def get_variable_names(self):
"""Returns list of all variable names in this model.
Returns:
List of names.
"""
return [name for name, _ in checkpoints.list_variables(self.model_dir)]
def print_tensors_in_checkpoint_file(file_name, tensor_name):
"""Prints tensors in a checkpoint file.
If no `tensor_name` is provided, prints the tensor names and shapes
in the checkpoint file.
If `tensor_name` is provided, prints the content of the tensor.
Args:
file_name: Name of the checkpoint file.
tensor_name: Name of the tensor in the checkpoint file to print.
"""
try:
if not tensor_name:
variables = checkpoints.list_variables(file_name)
for name, shape in variables:
print("%s\t%s" % (name, str(shape)))
else:
print("tensor_name: ", tensor_name)
print(checkpoints.load_variable(file_name, tensor_name))
except Exception as e: # pylint: disable=broad-except
print(str(e))
if "corrupted compressed block contents" in str(e):
print("It's likely that your checkpoint file has been compressed "
"with SNAPPY.")
def testGetAllVariables(self):
checkpoint_dir = self.get_temp_dir()
with self.test_session() as session:
_create_checkpoints(session, checkpoint_dir)
self.assertEqual(checkpoints.list_variables(checkpoint_dir),
[("useful_scope/var4", [9, 9]),
("var1", [1, 10]),
("var2", [10, 10]),
("var3", [100, 100])])
def weights_(self):
values = {}
optimizer_regex = r".*/" + self._optimizer.get_name() + r"(_\d)?$"
for name, _ in checkpoints.list_variables(self._model_dir):
if name.startswith("linear/") and name != "linear/bias_weight" and not re.match(optimizer_regex, name):
values[name] = checkpoints.load_variable(self._model_dir, name)
if len(values) == 1:
return values[list(values.keys())[0]]
return values
def weights_(self):
values = {}
optimizer_regex = r".*/" + self._optimizer.get_name() + r"(_\d)?$"
for name, _ in checkpoints.list_variables(self._model_dir):
if (name.startswith("linear/") and name != "linear/bias_weight"
and not re.match(optimizer_regex, name)):
values[name] = checkpoints.load_variable(self._model_dir, name)
if len(values) == 1:
return values[list(values.keys())[0]]
return values
def get_weights(self, model_dir):
"""Returns weights per feature of the linear part.
Args:
model_dir: Directory where model parameters, graph and etc. are saved.
Returns:
The weights created by this model (without the optimizer weights).
"""
all_variables = [name for name, _ in checkpoints.list_variables(model_dir)]
values = {}
optimizer_regex = r".*/" + self._get_optimizer().get_name() + r"(_\d)?$"
for name in all_variables:
if (name.startswith(self._scope + "/") and
name != self._scope + "/bias_weight" and
not re.match(optimizer_regex, name)):
values[name] = checkpoints.load_variable(model_dir, name)
if len(values) == 1:
return values[list(values.keys())[0]]
return values
def get_weights(self, model_dir):
"""Returns weights per feature of the linear part.
Args:
model_dir: Directory where model parameters, graph and etc. are saved.
Returns:
The weights created by this model (without the optimizer weights).
"""
all_variables = [
name for name, _ in checkpoints.list_variables(model_dir)
]
values = {}
optimizer_regex = r".*/" + self._get_optimizer().get_name(
) + r"(_\d)?$"
for name in all_variables:
if (name.startswith(self._scope + "/")
and name != self._scope + "/bias_weight"
and not re.match(optimizer_regex, name)):
values[name] = checkpoints.load_variable(model_dir, name)
if len(values) == 1:
return values[list(values.keys())[0]]
return values
def get_variable_names(self): return [name for name, _ in checkpoints.list_variables(self._model_dir)]
def get_variable_names(self): return [name for name, _ in checkpoints.list_variables(self._model_dir)]
