def init_weights(weights):
print(17.72)
ops = []
ca_tuples_w = []
ca_tuples = []
for w in weights:
initializer = w.initializer
for input in initializer.inputs:
if "_cai_" in input.name:
ca_tuples_w.append (w)
ca_tuples.append ( (w.shape.as_list(), w.dtype.as_numpy_dtype) )
break
else:
ops.append (initializer)
print(17.73)
if len(ops) != 0:
nn.tf_sess.run (ops)
print(17.74)
if len(ca_tuples) != 0:
nn.batch_set_value( [*zip(ca_tuples_w, nn.initializers.ca.generate_batch (ca_tuples))] )
print(17.75)
def set_weights(self, new_weights):
weights = self.get_weights()
if len(weights) != len(new_weights):
raise ValueError('len of lists mismatch')
tuples = []
for w, new_w in zip(weights, new_weights):
if len(w.shape) != new_w.shape:
new_w = new_w.reshape(w.shape)
tuples.append((w, new_w))
nn.batch_set_value(tuples)
def load_weights(self, filename):
"""
returns True if file exists
"""
filepath = Path(filename)
if filepath.exists():
result = True
d_dumped = filepath.read_bytes()
d = pickle.loads(d_dumped)
else:
return False
weights = self.get_weights()
if self.name is None:
raise Exception("name must be defined.")
try:
tuples = []
for w in weights:
w_name_split = w.name.split('/')
if self.name != w_name_split[0]:
raise Exception("weight first name != Saveable.name")
sub_w_name = "/".join(w_name_split[1:])
w_val = d.get(sub_w_name, None)
if w_val is None:
#io.log_err(f"Weight {w.name} was not loaded from file {filename}")
tuples.append((w, w.initializer))
else:
w_val = np.reshape(w_val, w.shape.as_list())
tuples.append((w, w_val))
nn.batch_set_value(tuples)
except:
return False
return True
