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Make GraphNetworkLayer subclass from tf.Module #337

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Merged
boomanaiden154 merged 4 commits into from
May 3, 2025
Merged

Make GraphNetworkLayer subclass from tf.Module #337

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7a05c32
[𝘀𝗽𝗿] changes to main this commit is based on
boomanaiden154 Apr 26, 2025
19a7b52
[𝘀𝗽𝗿] initial version
boomanaiden154 Apr 26, 2025
2d8c5bb
[𝘀𝗽𝗿] changes introduced through rebase
boomanaiden154 Apr 28, 2025
b868947
rebase
boomanaiden154 Apr 28, 2025
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10 changes: 2 additions & 8 deletions gematria/granite/python/gnn_model_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,8 +30,8 @@
import tf_keras


@dataclasses.dataclass(frozen=True)
class GraphNetworkLayer:
@dataclasses.dataclass
class GraphNetworkLayer(tf.Module):
"""Specifies one segment of the pipeline of the graph network.

Each segment consists of a graph network module, i.e. a Sonnet module that
Expand Down Expand Up @@ -290,12 +290,6 @@ def initialize(self):
tf_keras.layers.LayerNormalization(name=globals_layer_norm_name)
)

def _get_trainable_variables(self):
trainable_variables = list(super()._get_trainable_variables())
for layer in self._graph_network:
trainable_variables.extend(layer.module.trainable_variables)
return trainable_variables

# @Override
def _forward(self, feed_dict):
graph_tuple_outputs = self._execute_graph_network(feed_dict)
Expand Down
6 changes: 1 addition & 5 deletions gematria/model/python/model_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1331,9 +1331,6 @@ def compute_loss_tensor(self, schedule: FeedDict):
)
)

def _get_trainable_variables(self):
return self.trainable_variables

def train_batch(
self,
schedule: FeedDict,
Expand Down Expand Up @@ -1367,11 +1364,10 @@ def train_batch(
for variable in self._variable_groups.get(variable_group)
)

trainable_variables = self._get_trainable_variables()
variables = (
[variable.deref() for variable in requested_variables]
if requested_variables
else trainable_variables
else self.trainable_variables
)

grads = tape.gradient(loss_tensor, variables)
Expand Down