Adjust notebooks examples

examples/notebook/onnxruntime/Quick_Started_Notebook_of_INC_for_ONNXRuntime.ipynb

@@ -47,13 +47,14 @@
    "outputs": [],
    "source": [
     "# install neural-compressor from source\n",
+    "import sys\n",
     "!git clone https://github.com/intel/neural-compressor.git\n",
     "%cd ./neural-compressor\n",
-    "!pip install -r requirements.txt\n",
-    "!python setup.py install\n",
+    "!{sys.executable} -m pip install -r requirements.txt\n",
+    "!{sys.executable} setup.py install\n",
     "%cd ..\n",
     "# or install stable basic version from pypi\n",
-    "# pip install neural-compressor"
+    "# pip install neural-compressor\n"
    ]
   },
   {
@@ -65,10 +66,8 @@
    },
    "outputs": [],
    "source": [
-    "# install onnx related packages\n",
-    "!pip install onnx onnxruntime onnxruntime-extensions\n",
-    "# install other packages used in this notebook.\n",
-    "!pip install torch transformers accelerate coloredlogs sympy numpy sentencepiece protobuf optimum"
+    "# install required packages\n",
+    "!{sys.executable} install -r requirements.txt\n"
    ]
   },
   {
@@ -168,7 +167,7 @@
    "source": [
     "!export GLUE_DIR=./glue_data\n",
     "!wget https://raw.githubusercontent.com/Shimao-Zhang/Download_GLUE_Data/master/download_glue_data.py\n",
-    "!python download_glue_data.py --data_dir=GLUE_DIR --tasks=SST"
+    "!{sys.executable} download_glue_data.py --data_dir=GLUE_DIR --tasks=SST\n"
    ]
   },
   {
@@ -193,7 +192,7 @@
     "int8_model_path = \"onnx-model/int8-model.onnx\"\n",
     "data_path = \"./GLUE_DIR/SST-2\"\n",
     "task = \"sst-2\"\n",
-    "batch_size = 8"
+    "batch_size = 8\n"
    ]
   },
   {
@@ -343,7 +342,7 @@
     "            label=label\n",
     "        )\n",
     "        features.append(feats)\n",
-    "    return features"
+    "    return features\n"
    ]
   },
   {
@@ -377,7 +376,7 @@
     "                      model_name_or_path=model_name_or_path,\n",
     "                      model_type=\"distilbert\",\n",
     "                      task=task)\n",
-    "dataloader = DataLoader(framework=\"onnxruntime\", dataset=dataset, batch_size=batch_size)"
+    "dataloader = DataLoader(framework=\"onnxruntime\", dataset=dataset, batch_size=batch_size)\n"
    ]
   },
   {
@@ -448,7 +447,7 @@
     "        elif output_mode == \"regression\":\n",
     "            processed_preds = np.squeeze(self.pred_list)\n",
     "        result = transformers.glue_compute_metrics(self.task, processed_preds, self.label_list)\n",
-    "        return result[self.return_key[self.task]]"
+    "        return result[self.return_key[self.task]]\n"
    ]
   },
   {
@@ -486,7 +485,7 @@
     "            ort_inputs.update({inputs_names[i]: inputs[i]})\n",
     "        predictions = session.run(None, ort_inputs)\n",
     "        metric.update(predictions[0], labels)\n",
-    "    return metric.result()"
+    "    return metric.result()\n"
    ]
   },
   {
@@ -567,7 +566,7 @@
     "    num_heads=num_heads,\n",
     "    hidden_size=hidden_size,\n",
     "    optimization_options=opt_options)\n",
-    "model = model_optimizer.model"
+    "model = model_optimizer.model\n"
    ]
   },
   {
@@ -722,7 +721,7 @@
     "                           config,\n",
     "                           eval_func=eval_func,\n",
     "                           calib_dataloader=dataloader)\n",
-    "q_model.save(int8_model_path)"
+    "q_model.save(int8_model_path)\n"
    ]
   },
   {

examples/notebook/onnxruntime/requirements.txt

@@ -0,0 +1,12 @@
+onnx
+onnxruntime
+onnxruntime-extensions
+torch
+transformers
+accelerate
+coloredlogs
+sympy
+numpy
+sentencepiece
+protobuf
+optimum

examples/notebook/pytorch/Quick_Started_Notebook_of_INC_for_Pytorch.ipynb

@@ -45,14 +45,15 @@
    "outputs": [],
    "source": [
     "# install neural-compressor from source\n",
+    "import sys\n",
     "!git clone https://github.com/intel/neural-compressor.git\n",
     "%cd ./neural-compressor\n",
-    "!pip install -r requirements.txt\n",
-    "!python setup.py install\n",
+    "!{sys.executable} -m pip install -r requirements.txt\n",
+    "!{sys.executable} setup.py install\n",
     "%cd ..\n",
     "\n",
     "# or install stable basic version from pypi\n",
-    "!pip install neural-compressor"
+    "!{sys.executable} -m pip install neural-compressor\n"
    ]
   },
   {
@@ -62,7 +63,7 @@
    "outputs": [],
    "source": [
     "# install other packages used in this notebook.\n",
-    "!pip install torch>=1.9.0 transformers>=4.16.0 accelerate sympy numpy sentencepiece!=0.1.92 protobuf<=3.20.3 datasets>=1.1.3 scipy scikit-learn Keras-Preprocessing"
+    "!{sys.executable} -m pip install -r requirements.txt\n"
    ]
   },
   {
@@ -303,10 +304,10 @@
    "outputs": [],
    "source": [
     "# fp32 benchmark\n",
-    "!python benchmark.py --input_model ./pytorch_model.bin 2>&1|tee fp32_benchmark.log\n",
+    "!{sys.executable} benchmark.py --input_model ./pytorch_model.bin 2>&1|tee fp32_benchmark.log\n",
     "\n",
     "# int8 benchmark\n",
-    "!python benchmark.py --input_model ./saved_results/best_model.pt 2>&1|tee int8_benchmark.log\n"
+    "!{sys.executable} benchmark.py --input_model ./saved_results/best_model.pt 2>&1|tee int8_benchmark.log\n"
    ]
   }
  ],

examples/notebook/pytorch/requirements.txt

@@ -0,0 +1,11 @@
+torch>=1.9.0
+transformers>=4.16.0
+accelerate
+sympy
+numpy
+sentencepiece!=0.1.92
+protobuf<=3.20.3
+datasets>=1.1.3
+scipy
+scikit-learn
+Keras-Preprocessing

examples/notebook/tensorflow/resnet/requirements.txt

@@ -0,0 +1,8 @@
+numpy
+neural-compressor
+tensorflow
+datasets
+requests
+urllib3
+pyOpenSSL
+git+https://github.com/huggingface/huggingface_hub

examples/notebook/tensorflow/resnet/resnet_quantization.ipynb

@@ -29,12 +29,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import sys\n",
     "!conda install python==3.10 -y\n",
-    "!pip install neural-compressor\n",
-    "!wget -nc https://storage.googleapis.com/intel-optimized-tensorflow/models/v1_6/resnet50_fp32_pretrained_model.pb\n",
-    "!pip install tensorflow\n",
-    "!pip install datasets\n",
-    "!pip install git+https://github.com/huggingface/huggingface_hub"
+    "!{sys.executable} -m pip install -r requirements.txt \n",
+    "\n",
+    "!wget -nc https://storage.googleapis.com/intel-optimized-tensorflow/models/v1_6/resnet50_fp32_pretrained_model.pb\n"
    ]
   },
   {
@@ -43,9 +42,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "print(sys.executable)\n",
+    "!{sys.executable} -m pip list\n",
     "import tensorflow as tf\n",
     "import numpy as np\n",
-    "import datasets"
+    "import datasets\n"
    ]
   },
   {
@@ -63,8 +64,8 @@
    "source": [
     "# login to huggingface to download the imagenet-1k dataset\n",
     "# you should replace this read-only token with your own by create one on (https://huggingface.co/settings/tokens)\n",
-    "# !huggingface-cli login --token <YOUR HUGGINGFACE TOKEN>\n",
-    "!huggingface-cli login --token hf_xxxxxxxxxxxxxxxxxxxxxx"
+    "from huggingface_hub.hf_api import HfFolder\n",
+    "HfFolder.save_token('hf_xxxxxxxxxxxxxxxxxxxxxx')\n"
    ]
   },
   {
@@ -75,8 +76,8 @@
    "source": [
     "from datasets import load_dataset\n",
     "# load dataset in streaming way will get an IterableDatset\n",
-    "calib_dataset = load_dataset('imagenet-1k', split='train', streaming=True, use_auth_token=True)\n",
-    "eval_dataset = load_dataset('imagenet-1k', split='validation', streaming=True, use_auth_token=True)"
+    "calib_dataset = load_dataset('imagenet-1k', split='train', streaming=True, token=True)\n",
+    "eval_dataset = load_dataset('imagenet-1k', split='validation', streaming=True, token=True)\n"
    ]
   },
   {
@@ -97,7 +98,7 @@
     "    return datasets.Dataset.from_dict(data)\n",
     "\n",
     "sub_calib_dataset = sample_data(calib_dataset, MAX_SAMPLE_LENGTG)\n",
-    "sub_eval_dataset = sample_data(eval_dataset, MAX_SAMPLE_LENGTG)"
+    "sub_eval_dataset = sample_data(eval_dataset, MAX_SAMPLE_LENGTG)\n"
    ]
   },
   {
@@ -136,7 +137,7 @@
     "                batch_inputs = []\n",
     "                labels = []\n",
     "    def __len__(self):\n",
-    "        return self.length"
+    "        return self.length\n"
    ]
   },
   {
@@ -146,7 +147,7 @@
    "outputs": [],
    "source": [
     "calib_dataloader = CustomDataloader(dataset=sub_calib_dataset, batch_size=32)\n",
-    "eval_dataloader = CustomDataloader(dataset=sub_eval_dataset, batch_size=32)"
+    "eval_dataloader = CustomDataloader(dataset=sub_eval_dataset, batch_size=32)\n"
    ]
   },
   {
@@ -193,7 +194,7 @@
     "    return acc\n",
     "\n",
     "q_model = quantization.fit(\"./resnet50_fp32_pretrained_model.pb\", conf=conf, calib_dataloader=calib_dataloader, eval_func=eval_func)\n",
-    "q_model.save(\"resnet50_int8.pb\")"
+    "q_model.save(\"resnet50_int8.pb\")\n"
    ]
   },
   {
@@ -221,7 +222,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!python resnet_benchmark.py --input_model resnet50_fp32_pretrained_model.pb 2>&1|tee fp32_benchmark.log"
+    "!{sys.executable} resnet_benchmark.py --input_model resnet50_fp32_pretrained_model.pb 2>&1|tee fp32_benchmark.log\n"
    ]
   },
   {
@@ -237,7 +238,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!python resnet_benchmark.py --input_model resnet50_int8.pb 2>&1|tee int8_benchmark.log"
+    "!{sys.executable} resnet_benchmark.py --input_model resnet50_int8.pb 2>&1|tee int8_benchmark.log\n"
    ]
   },
   {

examples/notebook/tensorflow/vgg19_ibean/requirements.txt

@@ -0,0 +1,5 @@
+numpy
+matplotlib
+tensorflow
+tensorflow-hub
+tensorflow-datasets