Fix tensorboard related functions (13445738) · Commits · github_fork / Stable Diffusion Webui

modules/hypernetworks/hypernetwork.py

+6 −7

Original line number	Diff line number	Diff line
		@@ -561,7 +561,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
		_loss_step = 0 #internal
		# size = len(ds.indexes)
		# loss_dict = defaultdict(lambda : deque(maxlen = 1024))
		loss_logging = []
		loss_logging = deque(maxlen=len(ds) * 3) # this should be configurable parameter, this is 3 * epoch(dataset size)
		# losses = torch.zeros((size,))
		# previous_mean_losses = [0]
		# previous_mean_loss = 0
		@@ -602,7 +602,6 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
		else:
		c = stack_conds(batch.cond).to(devices.device, non_blocking=pin_memory)
		loss = shared.sd_model(x, c)[0] / gradient_step
		loss_logging.append(loss.item())
		del x
		del c

		@@ -612,7 +611,7 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
		# go back until we reach gradient accumulation steps
		if (j + 1) % gradient_step != 0:
		continue

		loss_logging.append(_loss_step)
		if clip_grad:
		clip_grad(weights, clip_grad_sched.learn_rate)

		@@ -691,9 +690,6 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
		processed = processing.process_images(p)
		image = processed.images[0] if len(processed.images) > 0 else None

		if shared.opts.training_enable_tensorboard and shared.opts.training_tensorboard_save_images:
		textual_inversion.tensorboard_add_image(tensorboard_writer, f"Validation at epoch {epoch_num}", image, hypernetwork.step)

		if unload:
		shared.sd_model.cond_stage_model.to(devices.cpu)
		shared.sd_model.first_stage_model.to(devices.cpu)
		@@ -703,7 +699,10 @@ def train_hypernetwork(id_task, hypernetwork_name, learn_rate, batch_size, gradi
		hypernetwork.train()
		if image is not None:
		shared.state.assign_current_image(image)

		if shared.opts.training_enable_tensorboard and shared.opts.training_tensorboard_save_images:
		textual_inversion.tensorboard_add_image(tensorboard_writer,
		f"Validation at epoch {epoch_num}", image,
		hypernetwork.step)
		last_saved_image, last_text_info = images.save_image(image, images_dir, "", p.seed, p.prompt, shared.opts.samples_format, processed.infotexts[0], p=p, forced_filename=forced_filename, save_to_dirs=False)
		last_saved_image += f", prompt: {preview_text}"

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