Ubuntu commited on
Commit
ec6657c
·
1 Parent(s): 034cfa9

serve loras update for logging

Browse files
Files changed (1) hide show
  1. serve_loras.py +16 -2
serve_loras.py CHANGED
@@ -1,6 +1,7 @@
1
  from compel import Compel, ReturnedEmbeddingsType
2
  import logging
3
  from abc import ABC
 
4
 
5
  import diffusers
6
  import torch
@@ -24,6 +25,9 @@ import os
24
  logger = logging.getLogger(__name__)
25
  logger.info("Diffusers version %s", diffusers.__version__)
26
 
 
 
 
27
  sentry_sdk.init(
28
  dsn="https://f750d1b039d66541f344ee6151d38166@o4505891057696768.ingest.sentry.io/4506071735205888",
29
  )
@@ -37,6 +41,7 @@ class DiffusersHandler(ABC):
37
 
38
  def __init__(self):
39
  self.initialized = False
 
40
 
41
  def initialize(self, properties):
42
  """In this initialize function, the Stable Diffusion model is loaded and
@@ -51,6 +56,7 @@ class DiffusersHandler(ABC):
51
 
52
 
53
  device_str = "cuda:" + str(properties.get("gpu_id")) if torch.cuda.is_available() and properties.get("gpu_id") is not None else "cpu"
 
54
 
55
  print("my device is " + device_str)
56
  self.device = torch.device(device_str)
@@ -65,6 +71,7 @@ class DiffusersHandler(ABC):
65
 
66
  logger.info(self.device)
67
  logger.info("Diffusion model from path %s loaded successfully")
 
68
 
69
  self.initialized = True
70
 
@@ -91,6 +98,7 @@ class DiffusersHandler(ABC):
91
  }
92
 
93
  logger.info("Processed request: '%s'", processed_request)
 
94
  return processed_request
95
 
96
 
@@ -125,6 +133,7 @@ class DiffusersHandler(ABC):
125
  self.pipe.unload_lora_weights()
126
 
127
  logger.info("Generated image: '%s'", inferences)
 
128
  return inferences
129
 
130
  def postprocess(self, inference_outputs):
@@ -152,8 +161,9 @@ class DiffusersHandler(ABC):
152
  # generate txt file with the image name and the prompt inside
153
  # blob = bucket.blob(image_name + '.txt')
154
  # blob.upload_from_string(self.prompt)
155
-
156
- outputs.append('https://storage.googleapis.com/' + bucket_name + '/' + image_name + '.png')
 
157
  return outputs
158
 
159
 
@@ -173,6 +183,7 @@ handler_index = 0
173
 
174
  @app.route('/generate', methods=['POST'])
175
  def generate_image():
 
176
  global handler_index
177
  try:
178
  # Extract raw requests from HTTP POST body
@@ -181,14 +192,17 @@ def generate_image():
181
  with handler_lock:
182
  selected_handler = handlers[handler_index]
183
  handler_index = (handler_index + 1) % gpu_count # Rotate to the next handler
 
184
 
185
  processed_request = selected_handler.preprocess([raw_requests])
186
  inferences = selected_handler.inference(processed_request)
187
  outputs = selected_handler.postprocess(inferences)
 
188
 
189
  return jsonify({"image_urls": outputs})
190
  except Exception as e:
191
  logger.error("Error during image generation: %s", str(e))
 
192
  return jsonify({"error": "Failed to generate image", "details": str(e)}), 500
193
 
194
  if __name__ == '__main__':
 
1
  from compel import Compel, ReturnedEmbeddingsType
2
  import logging
3
  from abc import ABC
4
+ import uuid
5
 
6
  import diffusers
7
  import torch
 
25
  logger = logging.getLogger(__name__)
26
  logger.info("Diffusers version %s", diffusers.__version__)
27
 
28
+ from axiom_logger import AxiomLogger
29
+ axiom_logger = AxiomLogger()
30
+
31
  sentry_sdk.init(
32
  dsn="https://f750d1b039d66541f344ee6151d38166@o4505891057696768.ingest.sentry.io/4506071735205888",
33
  )
 
41
 
42
  def __init__(self):
43
  self.initialized = False
44
+ self.req_id = None
45
 
46
  def initialize(self, properties):
47
  """In this initialize function, the Stable Diffusion model is loaded and
 
56
 
57
 
58
  device_str = "cuda:" + str(properties.get("gpu_id")) if torch.cuda.is_available() and properties.get("gpu_id") is not None else "cpu"
59
+ self.device_str = device_str
60
 
61
  print("my device is " + device_str)
62
  self.device = torch.device(device_str)
 
71
 
72
  logger.info(self.device)
73
  logger.info("Diffusion model from path %s loaded successfully")
74
+ axiom_logger.info("Diffusion model initialized", device=self.device_str)
75
 
76
  self.initialized = True
77
 
 
98
  }
99
 
100
  logger.info("Processed request: '%s'", processed_request)
101
+ axiom_logger.info("Processed request:" + str(processed_request), request_id=self.req_id, device=self.device_str)
102
  return processed_request
103
 
104
 
 
133
  self.pipe.unload_lora_weights()
134
 
135
  logger.info("Generated image: '%s'", inferences)
136
+ axiom_logger.info("Generated images", request_id=self.req_id, device=self.device_str)
137
  return inferences
138
 
139
  def postprocess(self, inference_outputs):
 
161
  # generate txt file with the image name and the prompt inside
162
  # blob = bucket.blob(image_name + '.txt')
163
  # blob.upload_from_string(self.prompt)
164
+ url_name = 'https://storage.googleapis.com/' + bucket_name + '/' + image_name + '.png'
165
+ outputs.append(url_name)
166
+ axiom_logger.info("Pushed image to google cloud: "+ url_name, request_id=self.req_id, device=self.device_str)
167
  return outputs
168
 
169
 
 
183
 
184
  @app.route('/generate', methods=['POST'])
185
  def generate_image():
186
+ req_id = str(uuid.uuid4())
187
  global handler_index
188
  try:
189
  # Extract raw requests from HTTP POST body
 
192
  with handler_lock:
193
  selected_handler = handlers[handler_index]
194
  handler_index = (handler_index + 1) % gpu_count # Rotate to the next handler
195
+ selected_handler.req_id = req_id
196
 
197
  processed_request = selected_handler.preprocess([raw_requests])
198
  inferences = selected_handler.inference(processed_request)
199
  outputs = selected_handler.postprocess(inferences)
200
+ selected_handler.req_id = None
201
 
202
  return jsonify({"image_urls": outputs})
203
  except Exception as e:
204
  logger.error("Error during image generation: %s", str(e))
205
+ axiom_logger.critical("Error during image generation: " + str(e), request_id=req_id)
206
  return jsonify({"error": "Failed to generate image", "details": str(e)}), 500
207
 
208
  if __name__ == '__main__':