add tests and edit deps

.github/workflows/test-studio.yml

@@ -0,0 +1,86 @@
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
+
+name: Validate Shark Studio
+
+on:
+  push:
+    branches: [ main ]
+    paths-ignore:
+      - '**.md'
+      - 'shark/examples/**'
+  pull_request:
+    branches: [ main ]
+    paths-ignore:
+      - '**.md'
+      - 'shark/examples/**'
+  workflow_dispatch:
+
+# Ensure that only a single job or workflow using the same
+# concurrency group will run at a time. This would cancel
+# any in-progress jobs in the same github workflow and github
+# ref (e.g. refs/heads/main or refs/pull/<pr_number>/merge).
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  build-validate:
+    strategy:
+      fail-fast: true
+      matrix:
+        os: [nodai-ubuntu-builder-large]
+        suite: [cpu] #,cuda,vulkan]
+        python-version: ["3.11"]
+        include:
+          - os: nodai-ubuntu-builder-large
+            suite: lint
+
+    runs-on: ${{ matrix.os }}
+
+    steps:
+    - uses: actions/checkout@v3
+
+    - name: Set Environment Variables
+      run: |
+        echo "SHORT_SHA=`git rev-parse --short=4 HEAD`" >> $GITHUB_ENV
+        echo "DATE=$(date +'%Y-%m-%d')" >> $GITHUB_ENV
+        
+    - name: Set up Python Version File ${{ matrix.python-version }}
+      run: |
+        echo ${{ matrix.python-version }} >> $GITHUB_WORKSPACE/.python-version
+    
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v4
+      with:
+        python-version: '${{ matrix.python-version }}'
+
+    - name: Install dependencies
+      if: matrix.suite == 'lint'
+      run: |
+        python -m pip install --upgrade pip
+        python -m pip install flake8 pytest toml black
+        
+    - name: Lint with flake8
+      if: matrix.suite == 'lint'
+      run: |
+        # black format check
+        black --version
+        black --check apps/shark_studio 
+        # stop the build if there are Python syntax errors or undefined names
+        flake8 . --statistics
+        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
+        flake8 . --isolated --count --exit-zero --max-complexity=10 --max-line-length=127 \
+          --statistics --exclude lit.cfg.py
+
+    - name: Validate Models on CPU
+      if: matrix.suite == 'cpu'
+      run: |
+        cd $GITHUB_WORKSPACE
+        python${{ matrix.python-version }} -m venv shark.venv
+        source shark.venv/bin/activate
+        pip install -r requirements.txt
+        pip install -e .
+        pip uninstall -y torch
+        pip install torch==2.1.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
+        python apps/shark_studio/tests/api_test.py

apps/shark_studio/api/llm.py

@@ -64,8 +64,7 @@ def __init__(
         self.use_system_prompt = use_system_prompt
         self.global_iter = 0
         if os.path.exists(self.vmfb_name) and (
-            os.path.exists(self.external_weight_file)
-            or external_weights is None
+            os.path.exists(self.external_weight_file) or external_weights is None
         ):
             self.iree_module_dict = dict()
             (
@@ -85,9 +84,7 @@ def __init__(
                 token=hf_auth_token,
             )
         elif not os.path.exists(self.tempfile_name):
-            self.torch_ir, self.tokenizer = llm_model_map[model_name][
-                "initializer"
-            ](
+            self.torch_ir, self.tokenizer = llm_model_map[model_name]["initializer"](
                 self.hf_model_name,
                 hf_auth_token,
                 compile_to="torch",
@@ -150,19 +147,15 @@ def format_out(results):
                         self.iree_module_dict["config"].device, input_tensor
                     )
                 ]
-                token = self.iree_module_dict["vmfb"]["run_initialize"](
-                    *device_inputs
-                )
+                token = self.iree_module_dict["vmfb"]["run_initialize"](*device_inputs)
             else:
                 device_inputs = [
                     ireert.asdevicearray(
                         self.iree_module_dict["config"].device,
                         token,
                     )
                 ]
-                token = self.iree_module_dict["vmfb"]["run_forward"](
-                    *device_inputs
-                )
+                token = self.iree_module_dict["vmfb"]["run_forward"](*device_inputs)
 
             total_time = time.time() - st_time
             history.append(format_out(token))

apps/shark_studio/api/utils.py

@@ -8,7 +8,5 @@ def get_available_devices():
 
 def get_resource_path(relative_path):
     """Get absolute path to resource, works for dev and for PyInstaller"""
-    base_path = getattr(
-        sys, "_MEIPASS", os.path.dirname(os.path.abspath(__file__))
-    )
+    base_path = getattr(sys, "_MEIPASS", os.path.dirname(os.path.abspath(__file__)))
     return os.path.join(base_path, relative_path)

apps/shark_studio/tests/api_test.py

@@ -0,0 +1,34 @@
+# Copyright 2023 Nod Labs, Inc
+#
+# Licensed under the Apache License v2.0 with LLVM Exceptions.
+# See https://llvm.org/LICENSE.txt for license information.
+# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+import logging
+import unittest
+from apps.shark_studio.api.llm import LanguageModel
+
+
+class LLMAPITest(unittest.TestCase):
+    def testLLMSimple(self):
+        lm = LanguageModel(
+            "Trelis/Llama-2-7b-chat-hf-function-calling-v2",
+            hf_auth_token=None,
+            device="cpu-task",
+            external_weights="safetensors",
+        )
+        count = 0
+        for msg, _ in lm.chat("hi, what are you?"):
+            # skip first token output
+            if count == 0:
+                count += 1
+                continue
+            assert (
+                msg.strip(" ") == "Hello"
+            ), f"LLM API failed to return correct response, expected 'Hello', received {msg}"
+            break
+
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.DEBUG)
+    unittest.main()

apps/shark_studio/web/index.py

@@ -93,9 +93,7 @@ def launch_app(address):
 
     def resource_path(relative_path):
         """Get absolute path to resource, works for dev and for PyInstaller"""
-        base_path = getattr(
-            sys, "_MEIPASS", os.path.dirname(os.path.abspath(__file__))
-        )
+        base_path = getattr(sys, "_MEIPASS", os.path.dirname(os.path.abspath(__file__)))
         return os.path.join(base_path, relative_path)
 
     dark_theme = resource_path("ui/css/sd_dark_theme.css")

apps/shark_studio/web/ui/chat.py

@@ -45,9 +45,7 @@ def create_prompt(model_name, history, prompt_prefix):
         msg = system_message + conversation
         msg = msg.strip()
     else:
-        conversation = "".join(
-            ["".join([item[0], item[1]]) for item in history]
-        )
+        conversation = "".join(["".join([item[0], item[1]]) for item in history])
         msg = system_message + conversation
         msg = msg.strip()
     return msg
@@ -65,9 +63,7 @@ def get_default_config():
         compilation_prompt,
         return_tensors="pt",
     ).input_ids
-    compilation_input_ids = torch.tensor(compilation_input_ids).reshape(
-        [1, 19]
-    )
+    compilation_input_ids = torch.tensor(compilation_input_ids).reshape([1, 19])
     firstVicunaCompileInput = (compilation_input_ids,)
     from apps.language_models.src.model_wrappers.vicuna_model import (
         CombinedModel,
@@ -138,17 +134,11 @@ def llm_chat_api(InputData: dict):
     #     print(f"prompt : {InputData['prompt']}")
     # print(f"max_tokens : {InputData['max_tokens']}") # Default to 128 for now
     global vicuna_model
-    model_name = (
-        InputData["model"] if "model" in InputData.keys() else "codegen"
-    )
+    model_name = InputData["model"] if "model" in InputData.keys() else "codegen"
     model_path = llm_model_map[model_name]
     device = "cpu-task"
     precision = "fp16"
-    max_toks = (
-        None
-        if "max_tokens" not in InputData.keys()
-        else InputData["max_tokens"]
-    )
+    max_toks = None if "max_tokens" not in InputData.keys() else InputData["max_tokens"]
     if max_toks is None:
         max_toks = 128 if model_name == "codegen" else 512
 
@@ -185,9 +175,7 @@ def llm_chat_api(InputData: dict):
     # TODO: add role dict for different models
     if is_chat_completion_api:
         # TODO: add funtionality for multiple messages
-        prompt = create_prompt(
-            model_name, [(InputData["messages"][0]["content"], "")]
-        )
+        prompt = create_prompt(model_name, [(InputData["messages"][0]["content"], "")])
     else:
         prompt = InputData["prompt"]
     print("prompt = ", prompt)
@@ -220,9 +208,7 @@ def llm_chat_api(InputData: dict):
     end_time = dt.now().strftime("%Y%m%d%H%M%S%f")
     return {
         "id": end_time,
-        "object": "chat.completion"
-        if is_chat_completion_api
-        else "text_completion",
+        "object": "chat.completion" if is_chat_completion_api else "text_completion",
         "created": int(end_time),
         "choices": choices,
     }
@@ -298,9 +284,7 @@ def view_json_file(file_obj):
 
     with gr.Row(visible=False):
         with gr.Group():
-            config_file = gr.File(
-                label="Upload sharding configuration", visible=False
-            )
+            config_file = gr.File(label="Upload sharding configuration", visible=False)
             json_view_button = gr.Button(label="View as JSON", visible=False)
         json_view = gr.JSON(interactive=True, visible=False)
         json_view_button.click(

build_tools/stable_diffusion_testing.py

@@ -36,9 +36,7 @@ def parse_sd_out(filename, command, device, use_tune, model_name, import_mlir):
                 metrics[val] = line.split(" ")[-1].strip("\n")
 
     metrics["Average step"] = metrics["Average step"].strip("ms/it")
-    metrics["Total image generation"] = metrics[
-        "Total image generation"
-    ].strip("sec")
+    metrics["Total image generation"] = metrics["Total image generation"].strip("sec")
     metrics["device"] = device
     metrics["use_tune"] = use_tune
     metrics["model_name"] = model_name
@@ -84,10 +82,14 @@ def test_loop(
     ]
     import_options = ["--import_mlir", "--no-import_mlir"]
     prompt_text = "--prompt=cyberpunk forest by Salvador Dali"
-    inpaint_prompt_text = "--prompt=Face of a yellow cat, high resolution, sitting on a park bench"
+    inpaint_prompt_text = (
+        "--prompt=Face of a yellow cat, high resolution, sitting on a park bench"
+    )
     if os.name == "nt":
         prompt_text = '--prompt="cyberpunk forest by Salvador Dali"'
-        inpaint_prompt_text = '--prompt="Face of a yellow cat, high resolution, sitting on a park bench"'
+        inpaint_prompt_text = (
+            '--prompt="Face of a yellow cat, high resolution, sitting on a park bench"'
+        )
     if beta:
         extra_flags.append("--beta_models=True")
     extra_flags.append("--no-progress_bar")
@@ -174,9 +176,7 @@ def test_loop(
                     )
                     print(command)
                     print("Successfully generated image")
-                    os.makedirs(
-                        "./test_images/golden/" + model_name, exist_ok=True
-                    )
+                    os.makedirs("./test_images/golden/" + model_name, exist_ok=True)
                     download_public_file(
                         "gs://shark_tank/testdata/golden/" + model_name,
                         "./test_images/golden/" + model_name,
@@ -191,14 +191,10 @@ def test_loop(
                     )
                     test_file = glob(test_file_path)[0]
 
-                    golden_path = (
-                        "./test_images/golden/" + model_name + "/*.png"
-                    )
+                    golden_path = "./test_images/golden/" + model_name + "/*.png"
                     golden_file = glob(golden_path)[0]
                     try:
-                        compare_images(
-                            test_file, golden_file, upload=upload_bool
-                        )
+                        compare_images(test_file, golden_file, upload=upload_bool)
                     except AssertionError as e:
                         print(e)
                         if exit_on_fail == True:
@@ -267,9 +263,7 @@ def prepare_artifacts():
 parser.add_argument(
     "-x", "--exit_on_fail", action=argparse.BooleanOptionalAction, default=True
 )
-parser.add_argument(
-    "-g", "--gen", action=argparse.BooleanOptionalAction, default=False
-)
+parser.add_argument("-g", "--gen", action=argparse.BooleanOptionalAction, default=False)
 
 if __name__ == "__main__":
     args = parser.parse_args()