edugp commited on
Commit
52a4ec3
1 Parent(s): caaaeef

Cache model and tokenizer and lock dependencies

Browse files
Files changed (2) hide show
  1. app.py +19 -3
  2. requirements.txt +7 -7
app.py CHANGED
@@ -2,10 +2,10 @@ import os
2
  import sys
3
 
4
  import streamlit as st
 
5
  from huggingface_hub import snapshot_download
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  from transformers import AutoTokenizer
7
 
8
-
9
  LOCAL_PATH = snapshot_download("flax-community/clip-spanish")
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  sys.path.append(LOCAL_PATH)
11
 
@@ -15,16 +15,24 @@ from test_on_image import run_inference
15
 
16
  def save_file_to_disk(uplaoded_file):
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  temp_file = os.path.join("/tmp", uplaoded_file.name)
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- with open(temp_file,"wb") as f:
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  f.write(uploaded_file.getbuffer())
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  return temp_file
21
 
 
 
 
 
 
 
 
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  def load_tokenizer_and_model():
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  # load the saved model
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  tokenizer = AutoTokenizer.from_pretrained("dccuchile/bert-base-spanish-wwm-cased")
25
  model = FlaxHybridCLIP.from_pretrained(LOCAL_PATH)
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  return tokenizer, model
27
 
 
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  tokenizer, model = load_tokenizer_and_model()
29
 
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  st.title("Image-Caption Matching")
@@ -36,7 +44,15 @@ if uploaded_file is not None and text_input:
36
  try:
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  local_image_path = save_file_to_disk(uploaded_file)
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  score = run_inference(local_image_path, text_input, model, tokenizer).tolist()
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- st.image(uploaded_file, caption=text_input, width=None, use_column_width=None, clamp=False, channels='RGB', output_format='auto')
 
 
 
 
 
 
 
 
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  st.write(f"## Score: {score:.2f}")
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  finally:
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  if local_image_path:
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  import sys
3
 
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  import streamlit as st
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+ import transformers
6
  from huggingface_hub import snapshot_download
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  from transformers import AutoTokenizer
8
 
 
9
  LOCAL_PATH = snapshot_download("flax-community/clip-spanish")
10
  sys.path.append(LOCAL_PATH)
11
 
15
 
16
  def save_file_to_disk(uplaoded_file):
17
  temp_file = os.path.join("/tmp", uplaoded_file.name)
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+ with open(temp_file, "wb") as f:
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  f.write(uploaded_file.getbuffer())
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  return temp_file
21
 
22
+
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+ @st.cache(
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+ hash_funcs={
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+ transformers.models.bert.tokenization_bert_fast.BertTokenizerFast: id,
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+ FlaxHybridCLIP: id,
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+ }
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+ )
29
  def load_tokenizer_and_model():
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  # load the saved model
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  tokenizer = AutoTokenizer.from_pretrained("dccuchile/bert-base-spanish-wwm-cased")
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  model = FlaxHybridCLIP.from_pretrained(LOCAL_PATH)
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  return tokenizer, model
34
 
35
+
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  tokenizer, model = load_tokenizer_and_model()
37
 
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  st.title("Image-Caption Matching")
44
  try:
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  local_image_path = save_file_to_disk(uploaded_file)
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  score = run_inference(local_image_path, text_input, model, tokenizer).tolist()
47
+ st.image(
48
+ uploaded_file,
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+ caption=text_input,
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+ width=None,
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+ use_column_width=None,
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+ clamp=False,
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+ channels="RGB",
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+ output_format="auto",
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+ )
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  st.write(f"## Score: {score:.2f}")
57
  finally:
58
  if local_image_path:
requirements.txt CHANGED
@@ -1,8 +1,8 @@
1
- flax
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- huggingface_hub
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- jax
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  streamlit==0.84.1
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- torch
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- torchvision
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- transformers
8
- watchdog
1
+ flax==0.3.4
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+ huggingface-hub==0.0.12
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+ jax==0.2.17
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  streamlit==0.84.1
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+ torch==1.9.0
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+ torchvision==0.10.0
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+ transformers==4.8.2
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+ watchdog==2.1.3