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converting to tf2 #425

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converting to tf2 #425

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4 changes: 2 additions & 2 deletions python/deprecated/eval_sgf.py
100755 → 100644
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Original file line number Diff line number Diff line change
Expand Up @@ -118,12 +118,12 @@ def play(pla,loc):

print(board.to_string())

saver = tf.train.Saver(
saver = tf.compat.v1.train.Saver(
max_to_keep = 10000,
save_relative_paths = True,
)

with tf.Session() as session:
with tf.compat.v1.Session() as session:

if not debug:
saver.restore(session, modelpath)
Expand Down
12 changes: 6 additions & 6 deletions python/deprecated/export_model.py
100755 → 100644
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Original file line number Diff line number Diff line change
Expand Up @@ -49,7 +49,7 @@ def log(s):
model = Model(model_config)

total_parameters = 0
for variable in tf.trainable_variables():
for variable in tf.compat.v1.trainable_variables():
shape = variable.get_shape()
variable_parameters = 1
for dim in shape:
Expand All @@ -63,17 +63,17 @@ def log(s):

print("Testing", flush=True)

saver = tf.train.Saver(
saver = tf.compat.v1.train.Saver(
max_to_keep = 10000,
save_relative_paths = True,
)

#Some tensorflow options
#tfconfig = tf.ConfigProto(log_device_placement=False,device_count={'GPU': 0})
tfconfig = tf.ConfigProto(log_device_placement=False)
tfconfig = tf.compat.v1.ConfigProto(log_device_placement=False)
#tfconfig.gpu_options.allow_growth = True
#tfconfig.gpu_options.per_process_gpu_memory_fraction = 0.4
with tf.Session(config=tfconfig) as session:
with tf.compat.v1.Session(config=tfconfig) as session:
saver.restore(session, model_file)

sys.stdout.flush()
Expand All @@ -85,7 +85,7 @@ def log(s):
sys.stderr.flush()

if not for_cuda:
tf.train.write_graph(session.graph_def,export_dir,filename_prefix + ".graph.pb")
tf.io.write_graph(session.graph_def,export_dir,filename_prefix + ".graph.pb")
savepath = export_dir + "/" + filename_prefix
saver.save(session, savepath + ".weights")
with open(savepath + ".config.json","w") as f:
Expand All @@ -112,7 +112,7 @@ def writeln(s):
writeln(model.max_board_size) #y
writeln(model.num_input_features)

variables = dict((variable.name,variable) for variable in tf.global_variables())
variables = dict((variable.name,variable) for variable in tf.compat.v1.global_variables())
def get_weights(name):
return np.array(variables[name+":0"].eval())

Expand Down
8 changes: 4 additions & 4 deletions python/deprecated/find_poses.py
100755 → 100644
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Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,7 @@ def log(s):
policy_probs_output = tf.nn.softmax(model.policy_output)

total_parameters = 0
for variable in tf.trainable_variables():
for variable in tf.compat.v1.trainable_variables():
shape = variable.get_shape()
variable_parameters = 1
for dim in shape:
Expand Down Expand Up @@ -94,17 +94,17 @@ def log(s):
sgfhash_start = next_moves_start + next_moves_len
sgfhash_len = 8

saver = tf.train.Saver(
saver = tf.compat.v1.train.Saver(
max_to_keep = 10000,
save_relative_paths = True,
)

#Some tensorflow options
#tfconfig = tf.ConfigProto(log_device_placement=False,device_count={'GPU': 0})
tfconfig = tf.ConfigProto(log_device_placement=False)
tfconfig = tf.compat.v1.ConfigProto(log_device_placement=False)
#tfconfig.gpu_options.allow_growth = True
#tfconfig.gpu_options.per_process_gpu_memory_fraction = 0.4
with tf.Session(config=tfconfig) as session:
with tf.compat.v1.Session(config=tfconfig) as session:
saver.restore(session, model_file)

log("Began session, loaded model")
Expand Down
10 changes: 5 additions & 5 deletions python/deprecated/mixmodels.py
100755 → 100644
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Original file line number Diff line number Diff line change
Expand Up @@ -45,7 +45,7 @@ def volume(variable):

variables = {}
total_parameters = 0
for variable in tf.global_variables():
for variable in tf.compat.v1.global_variables():
variable_parameters = volume(variable)
total_parameters += variable_parameters
variables[variable.name] = variable
Expand All @@ -59,16 +59,16 @@ def volume(variable):

print("Testing", flush=True)

saver = tf.train.Saver(
saver = tf.compat.v1.train.Saver(
max_to_keep = 10000,
save_relative_paths = True,
)

count = 0
accum_weights = {}

tfconfig = tf.ConfigProto(log_device_placement=False)
with tf.Session(config=tfconfig) as session:
tfconfig = tf.compat.v1.ConfigProto(log_device_placement=False)
with tf.compat.v1.Session(config=tfconfig) as session:

for model_file in model_files:
saver.restore(session, model_file)
Expand All @@ -91,7 +91,7 @@ def run(fetches):

assign_ops = dict([(name,variables[name].assign(accum_weights[name])) for name in accum_weights])

with tf.Session(config=tfconfig) as session:
with tf.compat.v1.Session(config=tfconfig) as session:
session.run(assign_ops)
print("Saving to " + output_file)
saver.save(session, output_file)
Expand Down
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