dev <- Mlperf inference

.github/workflows/code-review.yml

@@ -1,22 +1,34 @@
+name: OpenAI Code Review
+
 on:
-  pull_request:
+  pull_request_target:
     types: [opened, synchronize]
+    paths:
+      - 'automation/**'
+      - 'script/**'
+      - '!**.md'
+
+permissions:
+  issues: write
+  pull-requests: write
 
 jobs:
-  code_review_job:
+  code_review:
     runs-on: ubuntu-latest
-    if: github.repository_owner == 'gateoverflow'
-    name: ChatGPT Code Review
+    if: github.repository_owner == 'gateoverflow' && github.event.pull_request.changed_files > 0
     steps:
-      - name: GenAI Code Review
-        uses: cirolini/genai-code-review@v2
-        with:
-          openai_api_key: ${{ secrets.openai_api_key }}
-          github_token: ${{ secrets.GITHUB_TOKEN }}
-          github_pr_id: ${{ github.event.number }}
-          openai_model: "GPT-4o" # optional
-          openai_temperature: 0.5 # optional
-          openai_max_tokens: 2048 # optional
-          mode: files # files or patch
-          language: en # optional, default is 'en'
-          custom_prompt: "" # optional
+      # Run code review via OpenAI 
+      # Step to run the OpenAI Code Review using the GATEOverflow action
+    - name: Run OpenAI Code Review
+      uses: GATEOverflow/genai-code-review@v1
+      with:
+        github_token: ${{ secrets.GITHUB_TOKEN }}  # GitHub token for authentication
+        openai_api_key: ${{ secrets.OPENAI_API_KEY }}  # OpenAI API key for accessing the GPT model
+        github_pr_id: ${{ github.event.pull_request.number }}  # ID of the pull request to review
+        openai_model: "gpt-4o"  # Model to use for the code review
+        openai_temperature: 0.5  # Temperature setting for the model's output
+        openai_max_tokens: 2048  # Maximum number of tokens for the model's response
+        mode: "files"  # Mode of review, can be "files" or "diff"
+        language: "en"  # Language for the review output
+        custom_prompt: "" # Optional custom prompt for the model
+      continue-on-error: true  # Allow the workflow to continue even if this step fails

.github/workflows/test-mlperf-inference-sdxl.yaml

@@ -2,7 +2,7 @@ name: MLPerf inference SDXL
 
 on:
   schedule:
-    - cron: "1 2 * * */3"
+    - cron: "1 2 * * *"
 
 jobs:
   build_reference:

.github/workflows/test-scc24-sdxl.yaml

@@ -2,7 +2,7 @@ name: MLPerf inference SDXL
 
 on:
   schedule:
-    - cron: "1 3 * * */3"
+    - cron: "43 1 * * *"
 
 jobs:
   build_reference:

script/app-mlperf-inference-mlcommons-python/_cm.yaml

@@ -185,8 +185,9 @@ deps:
   ## Pytorch (CPU)
   - tags: get,generic-python-lib,_torch
     names:
-    - ml-engine-pytorch
-    - pytorch
+      - torch
+      - ml-engine-pytorch
+      - pytorch
     skip_if_env:
       CM_MODEL:
         - dlrm-v2-99
@@ -838,6 +839,9 @@ variations:
       MLPERF_TVM_TORCH_QUANTIZED_ENGINE: qnnpack
     deps:
     - tags: get,generic-python-lib,_torch
+      names:
+        - torch
+        - pytorch
     - tags: get,tvm
       names:
       - tvm
@@ -865,7 +869,6 @@ variations:
 
   gptj_:
     deps:
-    - tags: get,generic-python-lib,_torch
     - tags: get,generic-python-lib,_package.datasets
     - tags: get,generic-python-lib,_package.attrs
     - tags: get,generic-python-lib,_package.accelerate
@@ -1099,6 +1102,10 @@ variations:
       - dlrm-src
     # to force the version
     - tags: get,generic-python-lib,_torch
+      names:
+        - torch
+        - pytorch
+        - ml-engine-pytorch
       version: "1.13.1"
     - tags: get,generic-python-lib,_mlperf_logging
     - tags: get,generic-python-lib,_opencv-python

script/app-mlperf-inference/_cm.yaml

@@ -385,6 +385,7 @@ variations:
       CM_IMAGENET_ACCURACY_DTYPE: int32
       CM_CNNDM_ACCURACY_DTYPE: int32
       CM_LIBRISPEECH_ACCURACY_DTYPE: int8
+      CM_DOCKER_USE_VIRTUAL_PYTHON: no
     prehook_deps:
       - names:
          - nvidia-original-mlperf-inference
@@ -1162,7 +1163,7 @@ variations:
       mlperf-inference-implementation:
         tags: _cuda
     deps:
-      - tags: get,cuda-devices
+      - tags: get,cuda-devices,_with-pycuda
         skip_if_env:
           CM_CUDA_DEVICE_PROP_GLOBAL_MEMORY:
             - "yes"

script/build-dockerfile/customize.py

@@ -180,8 +180,11 @@ def preprocess(i):
 
     f.write(EOL+'# Install python packages' + EOL)
     python = get_value(env, config, 'PYTHON', 'CM_DOCKERFILE_PYTHON')
-    f.write('RUN {} -m venv /home/cmuser/venv/cm'.format(python) + " " + EOL)
-    f.write('ENV PATH="/home/cmuser/venv/cm/bin:$PATH"' + EOL)
+
+    docker_use_virtual_python = env.get('CM_DOCKER_USE_VIRTUAL_PYTHON', "yes")
+    if str(docker_use_virtual_python).lower() not in [ "no", "0", "false"]:
+        f.write('RUN {} -m venv /home/cmuser/venv/cm'.format(python) + " " + EOL)
+        f.write('ENV PATH="/home/cmuser/venv/cm/bin:$PATH"' + EOL)
     #f.write('RUN . /opt/venv/cm/bin/activate' + EOL)
     f.write('RUN {} -m pip install '.format(python) + " ".join(get_value(env, config, 'python-packages')) + ' ' + pip_extra_flags + ' ' + EOL)
 

script/download-file/run.sh

@@ -1,61 +1,58 @@
 #!/bin/bash
 
-
+# Execute config command if it exists
 if [[ -n ${CM_DOWNLOAD_CONFIG_CMD} ]]; then
-  echo ""
-  echo "${CM_DOWNLOAD_CONFIG_CMD}"
-  eval "${CM_DOWNLOAD_CONFIG_CMD}"
-  test $? -eq 0 || exit $?
+  echo -e "\nExecuting: ${CM_DOWNLOAD_CONFIG_CMD}"
+  eval "${CM_DOWNLOAD_CONFIG_CMD}" || exit $?
 fi
 
+# Assume download is required by default
 require_download=1
 
-if [[ "${CM_DOWNLOAD_LOCAL_FILE_PATH}" != "" ]]; then
+# No download needed if a local file path is specified or the tool is 'cmutil'
+if [[ -n "${CM_DOWNLOAD_LOCAL_FILE_PATH}" || ${CM_DOWNLOAD_TOOL} == "cmutil" ]]; then
   require_download=0
 fi
 
-if [[ ${CM_DOWNLOAD_TOOL} == "cmutil" ]]; then
-  require_download=0
-
-elif [ -e "${CM_DOWNLOAD_DOWNLOADED_PATH}" ]; then
-  if [[ "${CM_DOWNLOAD_CHECKSUM_CMD}" != "" ]]; then
-    echo ""
-    echo "${CM_DOWNLOAD_CHECKSUM_CMD}"
-    eval "${CM_DOWNLOAD_CHECKSUM_CMD}"
-    if [ $? -ne 0 ]; then
-       # checksum not supposed to fail for locally given file
-       if [[ "${CM_DOWNLOAD_LOCAL_FILE_PATH}" != "" ]]; then
-          exit 1
-       else
-          CM_PRE_DOWNLOAD_CLEAN=true
-       fi
+# If the file exists, check the checksum if necessary
+if [[ -e "${CM_DOWNLOAD_DOWNLOADED_PATH}" && -n "${CM_DOWNLOAD_CHECKSUM_CMD}" ]]; then
+  echo -e "\nChecking checksum: ${CM_DOWNLOAD_CHECKSUM_CMD}"
+  eval "${CM_DOWNLOAD_CHECKSUM_CMD}"
+
+  if [[ $? -ne 0 ]]; then
+    # If the checksum fails, handle errors based on whether the file is local
+    if [[ -n "${CM_DOWNLOAD_LOCAL_FILE_PATH}" ]]; then
+      echo "Checksum failed for local file. Exiting."
+      exit 1
     else
-       require_download="0"
+      echo "Checksum failed. Marking for re-download."
+      CM_PRE_DOWNLOAD_CLEAN=true
     fi
+  else
+    # If checksum succeeds, no download is required
+    require_download=0
   fi
 fi
 
-if [[ ${require_download} == "1" ]]; then
+# Perform download if required
+if [[ ${require_download} == 1 ]]; then
   echo ""
-  if [ -n "${CM_PRE_DOWNLOAD_CLEAN}" ] && [ "${CM_PRE_DOWNLOAD_CLEAN,,}" != "false" ]; then
-    echo "${CM_PRE_DOWNLOAD_CLEAN_CMD}"
-    eval "${CM_PRE_DOWNLOAD_CLEAN_CMD}"
-  fi
 
-  echo ""
-  echo "${CM_DOWNLOAD_CMD}"
-  eval "${CM_DOWNLOAD_CMD}"
-  test $? -eq 0 || exit $?
+  # If a pre-download clean command is specified and needed, execute it
+  if [[ -n "${CM_PRE_DOWNLOAD_CLEAN}" && "${CM_PRE_DOWNLOAD_CLEAN,,}" != "false" ]]; then
+    echo "Executing pre-download clean: ${CM_PRE_DOWNLOAD_CLEAN_CMD}"
+    eval "${CM_PRE_DOWNLOAD_CLEAN_CMD}" || exit $?
+  fi
 
+  # Execute the download command
+  echo "Downloading: ${CM_DOWNLOAD_CMD}"
+  eval "${CM_DOWNLOAD_CMD}" || exit $?
 fi
 
-if [[ ${CM_DOWNLOAD_TOOL} == "cmutil" || ${require_download} == "1"  ]]; then
-  if [[ "${CM_DOWNLOAD_CHECKSUM_CMD}" != "" ]]; then
-      echo ""
-      echo "${CM_DOWNLOAD_CHECKSUM_CMD}"
-      eval "${CM_DOWNLOAD_CHECKSUM_CMD}"
-      test $? -eq 0 || exit $?
+# Verify checksum again if necessary
+if [[ ${CM_DOWNLOAD_TOOL} == "cmutil" || ${require_download} == 1 ]]; then
+  if [[ -n "${CM_DOWNLOAD_CHECKSUM_CMD}" ]]; then
+    echo -e "\nVerifying checksum after download: ${CM_DOWNLOAD_CHECKSUM_CMD}"
+    eval "${CM_DOWNLOAD_CHECKSUM_CMD}" || exit $?
   fi
 fi
-
-test $? -eq 0 || exit $?

script/get-cuda-devices/_cm.yaml

@@ -33,9 +33,25 @@ docker:
 
 new_env_keys:
 - CM_CUDA_DEVICE_*
+- CM_CUDA_NUM_DEVICES
 
 new_state_keys:
 - cm_cuda_device_prop
+- cm_cuda_devices_prop
+- cm_cuda_num_devices
 
 print_files_if_script_error:
 - tmp-run.out
+
+variations:
+  with-pycuda:
+    env:
+      CM_CUDA_DEVICES_DETECT_USING_PYCUDA: 'yes'
+    deps:
+      - tags: get,python3
+        names:
+          - python
+          - python3
+      - tags: get,generic-python-lib,_package.pycuda
+        names:
+          - pycuda

script/get-cuda-devices/customize.py

@@ -2,6 +2,15 @@
 import os
 import subprocess
 
+def preprocess(i):
+
+    env = i['env']
+
+    if str(env.get('CM_CUDA_DEVICES_DETECT_USING_PYCUDA', '')).lower() in [ "1", "yes", "true"]:
+        i['run_script_input']['script_name'] = 'detect'
+
+    return {'return':0} 
+
 def postprocess(i):
 
     env = i['env']
@@ -18,22 +27,36 @@ def postprocess(i):
 
     # properties
     p = {}
+    gpu = {}
+
+    gpu_id = -1
 
     for line in lst:
-        print (line)
+        #print (line)
 
         j = line.find(':')
+
         if j>=0:
-           key = line[:j].strip()
-           val = line[j+1:].strip()
+            key = line[:j].strip()
+            val = line[j+1:].strip()
+
+            if key == "GPU Device ID":
+                gpu_id+=1
+                gpu[gpu_id] = {}
 
-           p[key] = val
+            if gpu_id < 0:
+                continue
 
-           key_env = 'CM_CUDA_DEVICE_PROP_'+key.upper().replace(' ','_')
-           env[key_env] = val
+            gpu[gpu_id][key] = val 
+            p[key] = val
+
+            key_env = 'CM_CUDA_DEVICE_PROP_'+key.upper().replace(' ','_')
+            env[key_env] = val
 
+    state['cm_cuda_num_devices'] = gpu_id
+    env['CM_CUDA_NUM_DEVICES'] = gpu_id
 
     state['cm_cuda_device_prop'] = p
+    state['cm_cuda_devices_prop'] = gpu
 
-    return {'return':0}
-
+    return {'return':0} 

script/get-cuda-devices/detect.py

@@ -0,0 +1,47 @@
+import pycuda.driver as cuda
+import pycuda.autoinit
+
+def get_gpu_info():
+    num_gpus = cuda.Device.count()
+    all_gpu_info = []
+
+    for i in range(num_gpus):
+        device = cuda.Device(i)
+        cuda_runtime_version = cuda.get_version()
+        cuda_runtime_version_str = f"{cuda_runtime_version[0]}.{cuda_runtime_version[1]}"
+
+        gpu_info = {
+            "GPU Device ID": device.pci_bus_id(),
+            "GPU Name": device.name(),
+            "GPU compute capability": f"{device.compute_capability()[0]}.{device.compute_capability()[1]}",
+            "CUDA driver version": f"{cuda.get_driver_version() // 1000}.{(cuda.get_driver_version() % 1000) // 10}",
+            "CUDA runtime version": cuda_runtime_version_str,
+            "Global memory": device.total_memory(),
+            "Max clock rate": f"{device.get_attribute(cuda.device_attribute.CLOCK_RATE)} MHz",
+            "Total amount of shared memory per block": device.get_attribute(cuda.device_attribute.MAX_SHARED_MEMORY_PER_BLOCK),
+            "Total number of registers available per block": device.get_attribute(cuda.device_attribute.MAX_REGISTERS_PER_BLOCK),
+            "Warp size": device.get_attribute(cuda.device_attribute.WARP_SIZE),
+            "Maximum number of threads per multiprocessor": device.get_attribute(cuda.device_attribute.MAX_THREADS_PER_MULTIPROCESSOR),
+            "Maximum number of threads per block": device.get_attribute(cuda.device_attribute.MAX_THREADS_PER_BLOCK),
+            "Max dimension size of a thread block X": device.get_attribute(cuda.device_attribute.MAX_BLOCK_DIM_X),
+            "Max dimension size of a thread block Y": device.get_attribute(cuda.device_attribute.MAX_BLOCK_DIM_Y),
+            "Max dimension size of a thread block Z": device.get_attribute(cuda.device_attribute.MAX_BLOCK_DIM_Z),
+            "Max dimension size of a grid size X": device.get_attribute(cuda.device_attribute.MAX_GRID_DIM_X),
+            "Max dimension size of a grid size Y": device.get_attribute(cuda.device_attribute.MAX_GRID_DIM_Y),
+            "Max dimension size of a grid size Z": device.get_attribute(cuda.device_attribute.MAX_GRID_DIM_Z),
+        }
+
+        all_gpu_info.append(gpu_info)
+
+    return all_gpu_info
+
+
+# Print the GPU information for all available GPUs
+if __name__ == "__main__":
+    gpu_info_list = get_gpu_info()
+    with open ("tmp-run.out", "w") as f:
+        for idx, gpu_info in enumerate(gpu_info_list):
+            print(f"GPU {idx}:")
+            for key, value in gpu_info.items():
+                f.write(f"{key}: {value}\n")
+

script/get-cuda-devices/detect.sh

@@ -0,0 +1,4 @@
+#!/bin/bash
+
+${CM_PYTHON_BIN_WITH_PATH} ${CM_TMP_CURRENT_SCRIPT_PATH}/detect.py
+test $? -eq 0 || exit $?

script/get-ml-model-gptj/_cm.json

@@ -231,7 +231,7 @@
           "tags": "get,nvidia,scratch,space"
         },
         {
-          "tags": "get,cuda-devices"
+          "tags": "get,cuda-devices,_with-pycuda"
         },
         {
           "tags": "get,ml-model,gpt-j,_fp32,_pytorch",

script/get-ml-model-llama2/_cm.json

@@ -223,7 +223,7 @@
           "tags": "get,nvidia,scratch,space"
         },
         {
-          "tags": "get,cuda-devices"
+          "tags": "get,cuda-devices,_with-pycuda"
         },
         {
           "tags": "get,ml-model,llama2-70b,_fp32,_pytorch",