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pre-merge cleanup

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This commit is contained in:
Vladimir Mandic
2023-01-29 12:19:17 -05:00
parent ee410df5a5
commit 0fa1d29fca
2 changed files with 27 additions and 7 deletions
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modules/textual_inversion/textual_inversion.py
+8 -7
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@@ -228,9 +228,9 @@ class EmbeddingDatabase:
self.load_from_dir(embdir)
embdir.update()
# print(f"Textual inversion embeddings loaded({len(self.word_embeddings)}): {', '.join(self.word_embeddings.keys())}")
# if len(self.skipped_embeddings) > 0:
# print(f"Textual inversion embeddings skipped({len(self.skipped_embeddings)}): {', '.join(self.skipped_embeddings.keys())}")
print(f"Textual inversion embeddings loaded({len(self.word_embeddings)}): {', '.join(self.word_embeddings.keys())}")
if len(self.skipped_embeddings) > 0:
print(f"Textual inversion embeddings skipped({len(self.skipped_embeddings)}): {', '.join(self.skipped_embeddings.keys())}")
def find_embedding_at_position(self, tokens, offset):
token = tokens[offset]
@@ -278,7 +278,7 @@ def write_loss(log_directory, filename, step, epoch_len, values):
if shared.opts.training_write_csv_every == 0:
return
if step % epoch_len != 0:
if step % shared.opts.training_write_csv_every != 0:
return
write_csv_header = False if os.path.exists(os.path.join(log_directory, filename)) else True
@@ -360,7 +360,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
filename = os.path.join(shared.cmd_opts.embeddings_dir, f'{embedding_name}.pt')
log_directory = os.path.join(log_directory, embedding_name)
log_directory = os.path.join(log_directory, datetime.datetime.now().strftime("%Y-%m-%d"), embedding_name)
unload = shared.opts.unload_models_when_training
if save_embedding_every > 0:
@@ -510,8 +510,9 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
steps_done = embedding.step + 1
epoch_num = embedding.step // steps_per_epoch
epoch_step = embedding.step % steps_per_epoch
description = f"Training textual inversion step {embedding.step} loss: {loss_step:.5f} lr: {scheduler.learn_rate:.5f}"
description = f"Training textual inversion [Epoch {epoch_num}: {epoch_step+1}/{steps_per_epoch}] loss: {loss_step:.7f}"
pbar.set_description(description)
if embedding_dir is not None and steps_done % save_embedding_every == 0:
# Before saving, change name to match current checkpoint.
@@ -520,7 +521,7 @@ def train_embedding(id_task, embedding_name, learn_rate, batch_size, gradient_st
save_embedding(embedding, optimizer, checkpoint, embedding_name_every, last_saved_file, remove_cached_checksum=True)
embedding_yet_to_be_embedded = True
write_loss(log_directory, "train.csv", embedding.step, steps_per_epoch, {
write_loss(log_directory, "textual_inversion_loss.csv", embedding.step, steps_per_epoch, {
"loss": f"{loss_step:.7f}",
"learn_rate": scheduler.learn_rate
})
webui-macos-env.sh
+19
View File
@@ -0,0 +1,19 @@
#!/bin/bash
####################################################################
# macOS defaults #
# Please modify webui-user.sh to change these instead of this file #
####################################################################
if [[ -x "$(command -v python3.10)" ]]
then
python_cmd="python3.10"
fi
export install_dir="$HOME"
export COMMANDLINE_ARGS="--skip-torch-cuda-test --upcast-sampling --no-half-vae --use-cpu interrogate"
export TORCH_COMMAND="pip install torch==1.12.1 torchvision==0.13.1"
export K_DIFFUSION_REPO="https://github.com/brkirch/k-diffusion.git"
export K_DIFFUSION_COMMIT_HASH="51c9778f269cedb55a4d88c79c0246d35bdadb71"
export PYTORCH_ENABLE_MPS_FALLBACK=1
####################################################################