Merge pull request #2246 from peastman/tensorboard (7e745b93) · Commits · 钟慕尧 / deepchem

deepchem/models/callbacks.py

+2 −1

Original line number	Diff line number	Diff line
		@@ -78,7 +78,8 @@ class ValidationCallback(object):
		print(message, file=self.output_file)
		if model.tensorboard:
		for key in scores:
		model._log_value_to_tensorboard(tag=key, simple_value=scores[key])
		model._log_scalar_to_tensorboard(key, scores[key],
		model.get_global_step())
		if model.wandb:
		import wandb
		wandb.log(scores, step=step)

+6 −2

Original line number	Diff line number	Diff line
		@@ -431,8 +431,7 @@ class KerasModel(Model):
		for c in callbacks:
		c(self, current_step)
		if self.tensorboard and should_log:
		with self._summary_writer.as_default():
		tf.summary.scalar('loss', batch_loss, current_step)
		self._log_scalar_to_tensorboard('loss', batch_loss, current_step)
		if self.wandb and should_log:
		wandb.log({'loss': batch_loss}, step=current_step)

		@@ -1075,6 +1074,11 @@ class KerasModel(Model):
		"""Get the number of steps of fitting that have been performed."""
		return int(self._global_step)

		def _log_scalar_to_tensorboard(self, name: str, value: Any, step: int):
		"""Log a scalar value to Tensorboard."""
		with self._summary_writer.as_default():
		tf.summary.scalar(name, value, step)

		def _create_assignment_map(self,
		source_model: "KerasModel",
		include_top: bool = True,

+5 −1

Original line number	Diff line number	Diff line
		@@ -402,7 +402,7 @@ class TorchModel(Model):
		for c in callbacks:
		c(self, current_step)
		if self.tensorboard and should_log:
		self._summary_writer.add_scalar('loss', batch_loss, current_step)
		self._log_scalar_to_tensorboard('loss', batch_loss, current_step)
		if self.wandb and should_log:
		wandb.log({'loss': batch_loss}, step=current_step)

		@@ -983,6 +983,10 @@ class TorchModel(Model):
		"""Get the number of steps of fitting that have been performed."""
		return self._global_step

		def _log_scalar_to_tensorboard(self, name: str, value: Any, step: int):
		"""Log a scalar value to Tensorboard."""
		self._summary_writer.add_scalar(name, value, step)

		def _create_assignment_map(self,
		source_model: "TorchModel",
		include_top: bool = True,