更新paddle pytorch 测试

dcu/paddle_check.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "21761981-d2c1-43f4-86b9-1322a2567e65",
+   "metadata": {},
+   "source": [
+    "# DCU镜像检测-paddlepaddle\n",
+    "此脚本为paddlepaddle的DCU镜像通用检查脚本，更多项目和issue信息请参考[链接](https://developer.sourcefind.cn/codes/chenpangpang/gpu-base-image-test)。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "35dc434c-70c7-48ee-a6c7-0bc5f7c4d143",
+   "metadata": {},
+   "source": [
+    "## 一、线上版本检测"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7e466048-2868-459c-8442-6ec5cdbf76db",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "print(sys.path)\n",
+    "import paddle\n",
+    "print(paddle.__version__,'\\n',paddle.__dcu_version__)\n",
+    "import paddle\n",
+    "paddle.device.get_device()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "77fe3509-6429-4b4b-9757-6c2663d11330",
+   "metadata": {},
+   "source": [
+    "## 一、脚本检测"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5ca1ce5d-7c90-4a54-ae45-642112227a17",
+   "metadata": {},
+   "source": [
+    "### 2.1 检测环境配置"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "49b3b355-9afd-42cf-b354-629dba8aba92",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install paddlenlp ppdiffusers"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7eba7a55-7407-462d-9405-59df27cefd45",
+   "metadata": {},
+   "source": [
+    "### 2.2 版本检测"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d2e335b4-7a98-425d-ad67-395537956888",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!python ../paddle/base_test.py"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e456e88d-7394-4382-9efc-f983b1d95ba9",
+   "metadata": {},
+   "source": [
+    "### 2.3 文本模型检测"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "646dda99-2f5f-4a72-b412-da12c002ef6e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!python ../paddletest/text.py"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c083c135-9109-4112-ad9a-9f03b80e0981",
+   "metadata": {},
+   "source": [
+    "### 2.4 图像模型检测"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0cc8d224-d107-4048-8a6d-ce7363fa5cc2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!python ../paddletest/image.py"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

dcu/pytorch_check.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1588c7b3-e01b-40b7-b26d-c90559ce4355",
+   "metadata": {},
+   "source": [
+    "# DCU镜像检测-pytorch\n",
+    "此脚本为pytorch的DCU镜像通用检查脚本，更多项目和issue信息请参考[链接](https://developer.sourcefind.cn/codes/chenpangpang/gpu-base-image-test)。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "de0f0d91-c642-4a34-bb2a-1c7b482246c9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3b01123f-d38f-4078-9e4c-4770ead409b0",
+   "metadata": {},
+   "source": [
+    "## 一、线上版本检测\n",
+    "目前线上版本检测分为(1) torch 2.1.0 python 3.8 (2) torch 2.1.0 python 3.10 (3) python 2.3.0 三个版本的检测"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cb3d1d2b-eba3-4943-bc1c-84a4eeeddacf",
+   "metadata": {},
+   "source": [
+    "## 1.1 torch 2.1.0 python 3.8 检测"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8c9a395c-eefd-4053-aa38-e6bb69a1e2a8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.system(\"cat /etc/issue\")\n",
+    "import torch\n",
+    "print(torch.cuda.is_available())\n",
+    "import sys\n",
+    "print(sys.path)\n",
+    "import torch;print(torch.__version__,'\\n',torch.__dcu_version__)\n",
+    "import torchvision;print(torchvision.__version__,'\\n',torchvision.__dcu_version__)\n",
+    "import torch;print(torch.__version__,'\\n',torch.__dcu_version__)\n",
+    "import torchvision;print(torchvision.__version__,'\\n',torchvision.__dcu_version__)\n",
+    "import xformers;print(xformers.__version__,'\\n',xformers.__dcu_version__)\n",
+    "import lightop;print(lightop.__version__,'\\n',lightop.__dcu_version__)\n",
+    "import fastpt;print(fastpt.__version__,'\\n',fastpt.__dcu_version__)\n",
+    "import layer_check_pt;print(layer_check_pt.__version__,'\\n',layer_check_pt.__dcu_version__)\n",
+    "import flash_attn;print(flash_attn.__version__,'\\n',flash_attn.__dcu_version__)\n",
+    "import vllm;print(vllm.__version__,'\\n',vllm.__dcu_version__)\n",
+    "import torch;import lmslim;print(lmslim.__version__,'\\n',lmslim.__dcu_version__)\n",
+    "import xformers;print(xformers.__version__,'\\n',xformers.__dcu_version__)\n",
+    "import triton;print(triton.__version__,'\\n',triton.__dcu_version__)\n",
+    "import bitsandbytes;print(bitsandbytes.__version__,'\\n',bitsandbytes.__version__)\n",
+    "import diffusers;print(diffusers.__version__,'\\n',diffusers.__dcu_version__)\n",
+    "import lmdeploy;print(lmdeploy.__version__,'\\n',lmdeploy.__dcu_version__)\n",
+    "import torchaudio;print(torchaudio.__version__,'\\n',torchaudio.__dcu_version__)\n",
+    "import ctranslate2; print(ctranslate2.__version__,'\\n',ctranslate2.__dcu_version__)\n",
+    "import tinycudann\n",
+    "import fmoe; print(fmoe.__version__,'\\n',fmoe.__dcu_version__)\n",
+    "import pytorch3d; print(pytorch3d.__version__,'\\n',pytorch3d.__dcu_version__)\n",
+    "import faiss; print(faiss.__version__,'\\n',faiss.__dcu_version__)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a49bb205-254c-433c-8fa8-a9fecfbe1127",
+   "metadata": {},
+   "source": [
+    "## 1.2 torch 2.1.0 python 3.10 检测"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9d8fac07-cef4-48a8-af30-fff6902bb095",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.system(\"cat /etc/issue\")\n",
+    "import torch\n",
+    "print(torch.cuda.is_available())\n",
+    "import sys\n",
+    "print(sys.path)\n",
+    "import torch;print(torch.__version__,'\\n',torch.__dcu_version__)\n",
+    "import torchvision;print(torchvision.__version__,'\\n',torchvision.__dcu_version__)\n",
+    "import torch;print(torch.__version__,'\\n',torch.__dcu_version__)\n",
+    "import torchvision;print(torchvision.__version__,'\\n',torchvision.__dcu_version__)\n",
+    "import xformers;print(xformers.__version__,'\\n',xformers.__dcu_version__)\n",
+    "import lightop;print(lightop.__version__,'\\n',lightop.__dcu_version__)\n",
+    "import fastpt;print(fastpt.__version__,'\\n',fastpt.__dcu_version__)\n",
+    "import layer_check_pt;print(layer_check_pt.__version__,'\\n',layer_check_pt.__dcu_version__)\n",
+    "import flash_attn;print(flash_attn.__version__,'\\n',flash_attn.__dcu_version__)\n",
+    "import vllm;print(vllm.__version__,'\\n',vllm.__dcu_version__)\n",
+    "import torch;import lmslim;print(lmslim.__version__,'\\n',lmslim.__dcu_version__)\n",
+    "import xformers;print(xformers.__version__,'\\n',xformers.__dcu_version__)\n",
+    "import triton;print(triton.__version__,'\\n',triton.__dcu_version__)\n",
+    "import bitsandbytes;print(bitsandbytes.__version__,'\\n',bitsandbytes.__version__)\n",
+    "import diffusers;print(diffusers.__version__,'\\n',diffusers.__dcu_version__)\n",
+    "import aitemplate;print(aitemplate.__version__,'\\n',aitemplate.__version__)\n",
+    "import lmdeploy;print(lmdeploy.__version__,'\\n',lmdeploy.__dcu_version__)\n",
+    "import torchaudio;print(torchaudio.__version__,'\\n',torchaudio.__dcu_version__)\n",
+    "import ctranslate2; print(ctranslate2.__version__,'\\n',ctranslate2.__dcu_version__)\n",
+    "import tinycudann\n",
+    "import fmoe; print(fmoe.__version__,'\\n',fmoe.__dcu_version__)\n",
+    "import pytorch3d; print(pytorch3d.__version__,'\\n',pytorch3d.__dcu_version__)\n",
+    "import faiss; print(faiss.__version__,'\\n',faiss.__dcu_version__)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d43438d4-685f-4802-a084-82237a716986",
+   "metadata": {},
+   "source": [
+    "## 1.3 torch 2.3.0 检测"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e3f1877d-2950-4d71-8999-bc9700c12aa9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.system(\"cat /etc/issue\")\n",
+    "import torch\n",
+    "print(torch.cuda.is_available())\n",
+    "import sys\n",
+    "print(sys.path)\n",
+    "import torch;print(torch.__version__,'\\n',torch.__dcu_version__)\n",
+    "import torchvision;print(torchvision.__version__,'\\n',torchvision.__dcu_version__)\n",
+    "import torch;print(torch.__version__,'\\n',torch.__dcu_version__)\n",
+    "import torchvision;print(torchvision.__version__,'\\n',torchvision.__dcu_version__)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7d6b5669-7323-439a-81a9-fd4d22203374",
+   "metadata": {},
+   "source": [
+    "## 二、脚本检测"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d9d99812-1f39-4d09-b7c6-e4dad76512eb",
+   "metadata": {},
+   "source": [
+    "### 2.1 检测环境配置"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f1610376-0737-44c6-844a-2be500aea28f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install diffusers "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "80f1654b-8469-4ada-8a0f-751c1d68a046",
+   "metadata": {},
+   "source": [
+    "### 2.2 文本模型检测"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9fd76680-aee7-4f91-84cb-d4545797638f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!python ../pytorch/gpt2/infer.py"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc670a82-b5ce-497a-a23c-9407cc9cc545",
+   "metadata": {},
+   "source": [
+    "### 2.3 图像模型检测"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "791f559c-22f8-486e-b232-315198bec464",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!python ../pytorch/stable-diffusion-v1-4/infer.py"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

paddle/base_test.py

+import os
+import sys
+import paddle
+import subprocess
+import re
+
+os.system('cat /etc/issue')
+print('Python version:', sys.version)
+print('PaddlePaddle version:', paddle.__version__)
+
+version = paddle.__version__
+version_pattern = r"(\d+)\.(\d+)\.(\d+)"
+match = re.match(version_pattern, version)
+major_version, minor_version, patch_version = map(int, match.groups())
+
+if major_version >= 3 or (major_version >= 2 and minor_version >= 4):
+    gpu_available = paddle.device.is_compiled_with_cuda()
+    print('PaddlePaddle GPU available:', gpu_available)
+    cuda_version = paddle.version.cuda() if gpu_available else 'No CUDA available'
+    cudnn_version = paddle.version.cudnn() if gpu_available else 'No cuDNN available'
+    print('PaddlePaddle CUDA version:', cuda_version)
+    print('PaddlePaddle cuDNN version:', cudnn_version)
+
+elif major_version >= 2 and minor_version < 4:
+    gpu_available = paddle.device.is_compiled_with_cuda()
+    print('PaddlePaddle GPU available:', gpu_available)
+    cuda_version = subprocess.getoutput('nvcc --version')
+    print('CUDA Version:')
+    print(cuda_version)
+    cudnn_version = subprocess.getoutput('dpkg -l | grep cudnn')
+    print('\ncuDNN Version:')
+    print(cudnn_version)
+
+else:
+    gpu_available = paddle.fluid.core.is_compiled_with_cuda()
+    print('PaddlePaddle cuda available:', gpu_available)
+    cuda_version = subprocess.getoutput('nvcc --version')
+    print('CUDA Version:')
+    print(cuda_version)
+    cudnn_version = subprocess.getoutput('dpkg -l | grep cudnn')
+    print('\ncuDNN Version:')
+    print(cudnn_version)

paddle/hf_down.py

+# pip install huggingface-cli
+import os
+
+os.environ['HF_ENDPOINT'] = 'https://hf-mirror.com'
+
+model_list = [
+    "openai-community/gpt2",
+    "stabilityai/stable-diffusion-2-1",
+    "google-bert/bert-base-uncased"
+]
+
+os.system("pip install -U huggingface-hub")
+
+for model_path in model_list:
+    root_dir = os.path.basename(model_path)
+    os.system(
+        f"huggingface-cli download --resume-download  {model_path} --local-dir ./{root_dir}/{model_path} \
+        --local-dir-use-symlinks False")

paddle/image.py

+import sys
+import re
+import paddle
+import subprocess
+
+def check_version():
+    try:
+        version = paddle.__version__
+        version_pattern = r"(\d+)\.(\d+)\.(\d+)"
+        match = re.match(version_pattern, version)
+        major, minor, patch_version = map(int, match.groups())
+        return major, minor
+    except ImportError:
+        print("PaddlePaddle is not installed.")
+        sys.exit(1)
+
+major, minor = check_version()
+
+# PaddlePaddle 2.4及以上版本
+if major >= 3 or (major == 2 and minor >= 4):
+    from ppdiffusers import StableDiffusionPipeline
+
+    pipe = StableDiffusionPipeline.from_pretrained("./stable-diffusion-2")
+
+    paddle.seed(5232132133)
+    prompt = "a portrait of shiba inu with a red cap growing on its head. intricate. lifelike. soft light. sony a 7 r iv 5 5 mm. cinematic post - processing "
+    image = pipe(prompt, guidance_scale=7.5, height=768, width=768).images[0]
+
+    image.save("shiba_dog_with_a_red_cap.png")
+
+# PaddlePaddle 2.0到2.3版本
+elif 2 <= major < 3 and 0 <= minor < 4:
+    import paddle
+    import paddle.vision.transforms as T
+    from PIL import Image
+    import numpy as np
+    import json
+
+    model = paddle.vision.models.resnet50(pretrained=True)
+    model.eval()
+
+    def preprocess_image(image_path):
+        transform = T.Compose([
+            T.Resize(256),
+            T.CenterCrop(224),
+            T.ToTensor(),
+            T.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
+        ])
+        image = Image.open(image_path).convert('RGB')
+        image = transform(image)
+        image = paddle.unsqueeze(image, axis=0)
+        return image
+
+    def predict(model, image_tensor):
+        with paddle.no_grad():
+            logits = model(image_tensor)
+            probs = paddle.nn.functional.softmax(logits, axis=1).numpy()
+        return probs
+
+    def load_labels(filepath):
+        with open(filepath, "r") as f:
+            labels = json.load(f)
+        return labels
+
+    def display_top_predictions(probs, labels):
+        top5_idx = np.argsort(probs[0])[-5:][::-1]
+        for idx in top5_idx:
+            print(f"Class: {labels[idx]}, Probability: {probs[0][idx]:.4f}")
+
+    if __name__ == "__main__":
+        image_path = "human.jpg"
+        labels_path = "imagenet-simple-labels.json"
+        image_tensor = preprocess_image(image_path)
+        labels = load_labels(labels_path)
+        probs = predict(model, image_tensor)
+        display_top_predictions(probs, labels)
+
+# PaddlePaddle 2.0以下版本
+else:
+    import paddle.fluid as fluid
+    import numpy as np
+    from PIL import Image
+
+    class SimpleCNN(fluid.dygraph.Layer):
+        def __init__(self, num_classes=10):
+            super(SimpleCNN, self).__init__()
+            self.conv1 = fluid.dygraph.Conv2D(num_channels=3, num_filters=32, filter_size=3, stride=1, padding=1)
+            self.pool1 = fluid.dygraph.Pool2D(pool_size=2, pool_stride=2, pool_type='max')
+            self.conv2 = fluid.dygraph.Conv2D(num_channels=32, num_filters=64, filter_size=3, stride=1, padding=1)
+            self.pool2 = fluid.dygraph.Pool2D(pool_size=2, pool_stride=2, pool_type='max')
+            self.fc = fluid.dygraph.Linear(input_dim=64*8*8, output_dim=num_classes)
+
+        def forward(self, x):
+            x = self.conv1(x)
+            x = fluid.layers.relu(x)
+            x = self.pool1(x)
+            x = self.conv2(x)
+            x = fluid.layers.relu(x)
+            x = self.pool2(x)
+            x = fluid.layers.flatten(x, 1)
+            x = self.fc(x)
+            return x
+
+    def load_image(image_path):
+        img = Image.open(image_path)
+        img = img.resize((32, 32), Image.ANTIALIAS)
+        img = np.array(img).astype('float32') / 255.0
+        img = img.transpose((2, 0, 1))
+        img = np.expand_dims(img, axis=0)
+        return img
+
+    def infer(image_path, model):
+        with fluid.dygraph.guard():
+            img = load_image(image_path)
+            img = fluid.dygraph.to_variable(img)
+            prediction = model(img)
+            predicted_class = np.argmax(prediction.numpy())
+            return predicted_class
+
+    if __name__ == "__main__":
+        image_path = "human.jpg"
+        with fluid.dygraph.guard():
+            model = SimpleCNN(num_classes=10)
+            model.eval()
+            predicted_label = infer(image_path, model)
+            print(f"Predicted label: {predicted_label}")
+print("finish")

paddle/imagenet-simple-labels.json

+["tench",
+"goldfish",
+"great white shark",
+"tiger shark",
+"hammerhead shark",
+"electric ray",
+"stingray",
+"cock",
+"hen",
+"ostrich",
+"brambling",
+"goldfinch",
+"house finch",
+"junco",
+"indigo bunting",
+"American robin",
+"bulbul",
+"jay",
+"magpie",
+"chickadee",
+"American dipper",
+"kite",
+"bald eagle",
+"vulture",
+"great grey owl",
+"fire salamander",
+"smooth newt",
+"newt",
+"spotted salamander",
+"axolotl",
+"American bullfrog",
+"tree frog",
+"tailed frog",
+"loggerhead sea turtle",
+"leatherback sea turtle",
+"mud turtle",
+"terrapin",
+"box turtle",
+"banded gecko",
+"green iguana",
+"Carolina anole",
+"desert grassland whiptail lizard",
+"agama",
+"frilled-necked lizard",
+"alligator lizard",
+"Gila monster",
+"European green lizard",
+"chameleon",
+"Komodo dragon",
+"Nile crocodile",
+"American alligator",
+"triceratops",
+"worm snake",
+"ring-necked snake",
+"eastern hog-nosed snake",
+"smooth green snake",
+"kingsnake",
+"garter snake",
+"water snake",
+"vine snake",
+"night snake",
+"boa constrictor",
+"African rock python",
+"Indian cobra",
+"green mamba",
+"sea snake",
+"Saharan horned viper",
+"eastern diamondback rattlesnake",
+"sidewinder",
+"trilobite",
+"harvestman",
+"scorpion",
+"yellow garden spider",
+"barn spider",
+"European garden spider",
+"southern black widow",
+"tarantula",
+"wolf spider",
+"tick",
+"centipede",
+"black grouse",
+"ptarmigan",
+"ruffed grouse",
+"prairie grouse",
+"peacock",
+"quail",
+"partridge",
+"grey parrot",
+"macaw",
+"sulphur-crested cockatoo",
+"lorikeet",
+"coucal",
+"bee eater",
+"hornbill",
+"hummingbird",
+"jacamar",
+"toucan",
+"duck",
+"red-breasted merganser",
+"goose",
+"black swan",
+"tusker",
+"echidna",
+"platypus",
+"wallaby",
+"koala",
+"wombat",
+"jellyfish",
+"sea anemone",
+"brain coral",
+"flatworm",
+"nematode",
+"conch",
+"snail",
+"slug",
+"sea slug",
+"chiton",
+"chambered nautilus",
+"Dungeness crab",
+"rock crab",
+"fiddler crab",
+"red king crab",
+"American lobster",
+"spiny lobster",
+"crayfish",
+"hermit crab",
+"isopod",
+"white stork",
+"black stork",
+"spoonbill",
+"flamingo",
+"little blue heron",
+"great egret",
+"bittern",
+"crane (bird)",
+"limpkin",
+"common gallinule",
+"American coot",
+"bustard",
+"ruddy turnstone",
+"dunlin",
+"common redshank",
+"dowitcher",
+"oystercatcher",
+"pelican",
+"king penguin",
+"albatross",
+"grey whale",
+"killer whale",
+"dugong",
+"sea lion",
+"Chihuahua",
+"Japanese Chin",
+"Maltese",
+"Pekingese",
+"Shih Tzu",
+"King Charles Spaniel",
+"Papillon",
+"toy terrier",
+"Rhodesian Ridgeback",
+"Afghan Hound",
+"Basset Hound",
+"Beagle",
+"Bloodhound",
+"Bluetick Coonhound",
+"Black and Tan Coonhound",
+"Treeing Walker Coonhound",
+"English foxhound",
+"Redbone Coonhound",
+"borzoi",
+"Irish Wolfhound",
+"Italian Greyhound",
+"Whippet",
+"Ibizan Hound",
+"Norwegian Elkhound",
+"Otterhound",
+"Saluki",
+"Scottish Deerhound",
+"Weimaraner",
+"Staffordshire Bull Terrier",
+"American Staffordshire Terrier",
+"Bedlington Terrier",
+"Border Terrier",
+"Kerry Blue Terrier",
+"Irish Terrier",
+"Norfolk Terrier",
+"Norwich Terrier",
+"Yorkshire Terrier",
+"Wire Fox Terrier",
+"Lakeland Terrier",
+"Sealyham Terrier",
+"Airedale Terrier",
+"Cairn Terrier",
+"Australian Terrier",
+"Dandie Dinmont Terrier",
+"Boston Terrier",
+"Miniature Schnauzer",
+"Giant Schnauzer",
+"Standard Schnauzer",
+"Scottish Terrier",
+"Tibetan Terrier",
+"Australian Silky Terrier",
+"Soft-coated Wheaten Terrier",
+"West Highland White Terrier",
+"Lhasa Apso",
+"Flat-Coated Retriever",
+"Curly-coated Retriever",
+"Golden Retriever",
+"Labrador Retriever",
+"Chesapeake Bay Retriever",
+"German Shorthaired Pointer",
+"Vizsla",
+"English Setter",
+"Irish Setter",
+"Gordon Setter",
+"Brittany Spaniel",
+"Clumber Spaniel",
+"English Springer Spaniel",
+"Welsh Springer Spaniel",
+"Cocker Spaniels",
+"Sussex Spaniel",
+"Irish Water Spaniel",
+"Kuvasz",
+"Schipperke",
+"Groenendael",
+"Malinois",
+"Briard",
+"Australian Kelpie",
+"Komondor",
+"Old English Sheepdog",
+"Shetland Sheepdog",
+"collie",
+"Border Collie",
+"Bouvier des Flandres",
+"Rottweiler",
+"German Shepherd Dog",
+"Dobermann",
+"Miniature Pinscher",
+"Greater Swiss Mountain Dog",
+"Bernese Mountain Dog",
+"Appenzeller Sennenhund",
+"Entlebucher Sennenhund",
+"Boxer",
+"Bullmastiff",
+"Tibetan Mastiff",
+"French Bulldog",
+"Great Dane",
+"St. Bernard",
+"husky",
+"Alaskan Malamute",
+"Siberian Husky",
+"Dalmatian",
+"Affenpinscher",
+"Basenji",
+"pug",
+"Leonberger",
+"Newfoundland",
+"Pyrenean Mountain Dog",
+"Samoyed",
+"Pomeranian",
+"Chow Chow",
+"Keeshond",
+"Griffon Bruxellois",
+"Pembroke Welsh Corgi",
+"Cardigan Welsh Corgi",
+"Toy Poodle",
+"Miniature Poodle",
+"Standard Poodle",
+"Mexican hairless dog",
+"grey wolf",
+"Alaskan tundra wolf",
+"red wolf",
+"coyote",
+"dingo",
+"dhole",
+"African wild dog",
+"hyena",
+"red fox",
+"kit fox",
+"Arctic fox",
+"grey fox",
+"tabby cat",
+"tiger cat",
+"Persian cat",
+"Siamese cat",
+"Egyptian Mau",
+"cougar",
+"lynx",
+"leopard",
+"snow leopard",
+"jaguar",
+"lion",
+"tiger",
+"cheetah",
+"brown bear",
+"American black bear",
+"polar bear",
+"sloth bear",
+"mongoose",
+"meerkat",
+"tiger beetle",
+"ladybug",
+"ground beetle",
+"longhorn beetle",
+"leaf beetle",
+"dung beetle",
+"rhinoceros beetle",
+"weevil",
+"fly",
+"bee",
+"ant",
+"grasshopper",
+"cricket",
+"stick insect",
+"cockroach",
+"mantis",
+"cicada",
+"leafhopper",
+"lacewing",
+"dragonfly",
+"damselfly",
+"red admiral",
+"ringlet",
+"monarch butterfly",
+"small white",
+"sulphur butterfly",
+"gossamer-winged butterfly",
+"starfish",
+"sea urchin",
+"sea cucumber",
+"cottontail rabbit",
+"hare",
+"Angora rabbit",
+"hamster",
+"porcupine",
+"fox squirrel",
+"marmot",
+"beaver",
+"guinea pig",
+"common sorrel",
+"zebra",
+"pig",
+"wild boar",
+"warthog",
+"hippopotamus",
+"ox",
+"water buffalo",
+"bison",
+"ram",
+"bighorn sheep",
+"Alpine ibex",
+"hartebeest",
+"impala",
+"gazelle",
+"dromedary",
+"llama",
+"weasel",
+"mink",
+"European polecat",
+"black-footed ferret",
+"otter",
+"skunk",
+"badger",
+"armadillo",
+"three-toed sloth",
+"orangutan",
+"gorilla",
+"chimpanzee",
+"gibbon",
+"siamang",
+"guenon",
+"patas monkey",
+"baboon",
+"macaque",
+"langur",
+"black-and-white colobus",
+"proboscis monkey",
+"marmoset",
+"white-headed capuchin",
+"howler monkey",
+"titi",
+"Geoffroy's spider monkey",
+"common squirrel monkey",
+"ring-tailed lemur",
+"indri",
+"Asian elephant",
+"African bush elephant",
+"red panda",
+"giant panda",
+"snoek",
+"eel",
+"coho salmon",
+"rock beauty",
+"clownfish",
+"sturgeon",
+"garfish",
+"lionfish",
+"pufferfish",
+"abacus",
+"abaya",
+"academic gown",
+"accordion",
+"acoustic guitar",
+"aircraft carrier",
+"airliner",
+"airship",
+"altar",
+"ambulance",
+"amphibious vehicle",
+"analog clock",
+"apiary",
+"apron",
+"waste container",
+"assault rifle",
+"backpack",
+"bakery",
+"balance beam",
+"balloon",
+"ballpoint pen",
+"Band-Aid",
+"banjo",
+"baluster",
+"barbell",
+"barber chair",
+"barbershop",
+"barn",
+"barometer",
+"barrel",
+"wheelbarrow",
+"baseball",
+"basketball",
+"bassinet",
+"bassoon",
+"swimming cap",
+"bath towel",
+"bathtub",
+"station wagon",
+"lighthouse",
+"beaker",
+"military cap",
+"beer bottle",
+"beer glass",
+"bell-cot",
+"bib",
+"tandem bicycle",
+"bikini",
+"ring binder",
+"binoculars",
+"birdhouse",
+"boathouse",
+"bobsleigh",
+"bolo tie",
+"poke bonnet",
+"bookcase",
+"bookstore",
+"bottle cap",
+"bow",
+"bow tie",
+"brass",
+"bra",
+"breakwater",
+"breastplate",
+"broom",
+"bucket",
+"buckle",
+"bulletproof vest",
+"high-speed train",
+"butcher shop",
+"taxicab",
+"cauldron",
+"candle",
+"cannon",
+"canoe",
+"can opener",
+"cardigan",
+"car mirror",
+"carousel",
+"tool kit",
+"carton",
+"car wheel",
+"automated teller machine",
+"cassette",
+"cassette player",
+"castle",
+"catamaran",
+"CD player",
+"cello",
+"mobile phone",
+"chain",
+"chain-link fence",
+"chain mail",
+"chainsaw",
+"chest",
+"chiffonier",
+"chime",
+"china cabinet",
+"Christmas stocking",
+"church",
+"movie theater",
+"cleaver",
+"cliff dwelling",
+"cloak",
+"clogs",
+"cocktail shaker",
+"coffee mug",
+"coffeemaker",
+"coil",
+"combination lock",
+"computer keyboard",
+"confectionery store",
+"container ship",
+"convertible",
+"corkscrew",
+"cornet",
+"cowboy boot",
+"cowboy hat",
+"cradle",
+"crane (machine)",
+"crash helmet",
+"crate",
+"infant bed",
+"Crock Pot",
+"croquet ball",
+"crutch",
+"cuirass",
+"dam",
+"desk",
+"desktop computer",
+"rotary dial telephone",
+"diaper",
+"digital clock",
+"digital watch",
+"dining table",
+"dishcloth",
+"dishwasher",
+"disc brake",
+"dock",
+"dog sled",
+"dome",
+"doormat",
+"drilling rig",
+"drum",
+"drumstick",
+"dumbbell",
+"Dutch oven",
+"electric fan",
+"electric guitar",
+"electric locomotive",
+"entertainment center",
+"envelope",
+"espresso machine",
+"face powder",
+"feather boa",
+"filing cabinet",
+"fireboat",
+"fire engine",
+"fire screen sheet",
+"flagpole",
+"flute",
+"folding chair",
+"football helmet",
+"forklift",
+"fountain",
+"fountain pen",
+"four-poster bed",
+"freight car",
+"French horn",
+"frying pan",
+"fur coat",
+"garbage truck",
+"gas mask",
+"gas pump",
+"goblet",
+"go-kart",
+"golf ball",
+"golf cart",
+"gondola",
+"gong",
+"gown",
+"grand piano",
+"greenhouse",
+"grille",
+"grocery store",
+"guillotine",
+"barrette",
+"hair spray",
+"half-track",
+"hammer",
+"hamper",
+"hair dryer",
+"hand-held computer",
+"handkerchief",
+"hard disk drive",
+"harmonica",
+"harp",
+"harvester",
+"hatchet",
+"holster",
+"home theater",
+"honeycomb",
+"hook",
+"hoop skirt",
+"horizontal bar",
+"horse-drawn vehicle",
+"hourglass",
+"iPod",
+"clothes iron",
+"jack-o'-lantern",
+"jeans",
+"jeep",
+"T-shirt",
+"jigsaw puzzle",
+"pulled rickshaw",
+"joystick",
+"kimono",
+"knee pad",
+"knot",
+"lab coat",
+"ladle",
+"lampshade",
+"laptop computer",
+"lawn mower",
+"lens cap",
+"paper knife",
+"library",
+"lifeboat",
+"lighter",
+"limousine",
+"ocean liner",
+"lipstick",
+"slip-on shoe",
+"lotion",
+"speaker",
+"loupe",
+"sawmill",
+"magnetic compass",
+"mail bag",
+"mailbox",
+"tights",
+"tank suit",
+"manhole cover",
+"maraca",
+"marimba",
+"mask",
+"match",
+"maypole",
+"maze",
+"measuring cup",
+"medicine chest",
+"megalith",
+"microphone",
+"microwave oven",
+"military uniform",
+"milk can",
+"minibus",
+"miniskirt",
+"minivan",
+"missile",
+"mitten",
+"mixing bowl",
+"mobile home",
+"Model T",
+"modem",
+"monastery",
+"monitor",
+"moped",
+"mortar",
+"square academic cap",
+"mosque",
+"mosquito net",
+"scooter",
+"mountain bike",
+"tent",
+"computer mouse",
+"mousetrap",
+"moving van",
+"muzzle",
+"nail",
+"neck brace",
+"necklace",
+"nipple",
+"notebook computer",
+"obelisk",
+"oboe",
+"ocarina",
+"odometer",
+"oil filter",
+"organ",
+"oscilloscope",
+"overskirt",
+"bullock cart",
+"oxygen mask",
+"packet",
+"paddle",
+"paddle wheel",
+"padlock",
+"paintbrush",
+"pajamas",
+"palace",
+"pan flute",
+"paper towel",
+"parachute",
+"parallel bars",
+"park bench",
+"parking meter",
+"passenger car",
+"patio",
+"payphone",
+"pedestal",
+"pencil case",
+"pencil sharpener",
+"perfume",
+"Petri dish",
+"photocopier",
+"plectrum",
+"Pickelhaube",
+"picket fence",
+"pickup truck",
+"pier",
+"piggy bank",
+"pill bottle",
+"pillow",
+"ping-pong ball",
+"pinwheel",
+"pirate ship",
+"pitcher",
+"hand plane",
+"planetarium",
+"plastic bag",
+"plate rack",
+"plow",
+"plunger",
+"Polaroid camera",
+"pole",
+"police van",
+"poncho",
+"billiard table",
+"soda bottle",
+"pot",
+"potter's wheel",
+"power drill",
+"prayer rug",
+"printer",
+"prison",
+"projectile",
+"projector",
+"hockey puck",
+"punching bag",
+"purse",
+"quill",
+"quilt",
+"race car",
+"racket",
+"radiator",
+"radio",
+"radio telescope",
+"rain barrel",
+"recreational vehicle",
+"reel",
+"reflex camera",
+"refrigerator",
+"remote control",
+"restaurant",
+"revolver",
+"rifle",
+"rocking chair",
+"rotisserie",
+"eraser",
+"rugby ball",
+"ruler",
+"running shoe",
+"safe",
+"safety pin",
+"salt shaker",
+"sandal",
+"sarong",
+"saxophone",
+"scabbard",
+"weighing scale",
+"school bus",
+"schooner",
+"scoreboard",
+"CRT screen",
+"screw",
+"screwdriver",
+"seat belt",
+"sewing machine",
+"shield",
+"shoe store",
+"shoji",
+"shopping basket",
+"shopping cart",
+"shovel",
+"shower cap",
+"shower curtain",
+"ski",
+"ski mask",
+"sleeping bag",
+"slide rule",
+"sliding door",
+"slot machine",
+"snorkel",
+"snowmobile",
+"snowplow",
+"soap dispenser",
+"soccer ball",
+"sock",
+"solar thermal collector",
+"sombrero",
+"soup bowl",
+"space bar",
+"space heater",
+"space shuttle",
+"spatula",
+"motorboat",
+"spider web",
+"spindle",
+"sports car",
+"spotlight",
+"stage",
+"steam locomotive",
+"through arch bridge",
+"steel drum",
+"stethoscope",
+"scarf",
+"stone wall",
+"stopwatch",
+"stove",
+"strainer",
+"tram",
+"stretcher",
+"couch",
+"stupa",
+"submarine",
+"suit",
+"sundial",
+"sunglass",
+"sunglasses",
+"sunscreen",
+"suspension bridge",
+"mop",
+"sweatshirt",
+"swimsuit",
+"swing",
+"switch",
+"syringe",
+"table lamp",
+"tank",
+"tape player",
+"teapot",
+"teddy bear",
+"television",
+"tennis ball",
+"thatched roof",
+"front curtain",
+"thimble",
+"threshing machine",
+"throne",
+"tile roof",
+"toaster",
+"tobacco shop",
+"toilet seat",
+"torch",
+"totem pole",
+"tow truck",
+"toy store",
+"tractor",
+"semi-trailer truck",
+"tray",
+"trench coat",
+"tricycle",
+"trimaran",
+"tripod",
+"triumphal arch",
+"trolleybus",
+"trombone",
+"tub",
+"turnstile",
+"typewriter keyboard",
+"umbrella",
+"unicycle",
+"upright piano",
+"vacuum cleaner",
+"vase",
+"vault",
+"velvet",
+"vending machine",
+"vestment",
+"viaduct",
+"violin",
+"volleyball",
+"waffle iron",
+"wall clock",
+"wallet",
+"wardrobe",
+"military aircraft",
+"sink",
+"washing machine",
+"water bottle",
+"water jug",
+"water tower",
+"whiskey jug",
+"whistle",
+"wig",
+"window screen",
+"window shade",
+"Windsor tie",
+"wine bottle",
+"wing",
+"wok",
+"wooden spoon",
+"wool",
+"split-rail fence",
+"shipwreck",
+"yawl",
+"yurt",
+"website",
+"comic book",
+"crossword",
+"traffic sign",
+"traffic light",
+"dust jacket",
+"menu",
+"plate",
+"guacamole",
+"consomme",
+"hot pot",
+"trifle",
+"ice cream",
+"ice pop",
+"baguette",
+"bagel",
+"pretzel",
+"cheeseburger",
+"hot dog",
+"mashed potato",
+"cabbage",
+"broccoli",
+"cauliflower",
+"zucchini",
+"spaghetti squash",
+"acorn squash",
+"butternut squash",
+"cucumber",
+"artichoke",
+"bell pepper",
+"cardoon",
+"mushroom",
+"Granny Smith",
+"strawberry",
+"orange",
+"lemon",
+"fig",
+"pineapple",
+"banana",
+"jackfruit",
+"custard apple",
+"pomegranate",
+"hay",
+"carbonara",
+"chocolate syrup",
+"dough",
+"meatloaf",
+"pizza",
+"pot pie",
+"burrito",
+"red wine",
+"espresso",
+"cup",
+"eggnog",
+"alp",
+"bubble",
+"cliff",
+"coral reef",
+"geyser",
+"lakeshore",
+"promontory",
+"shoal",
+"seashore",
+"valley",
+"volcano",
+"baseball player",
+"bridegroom",
+"scuba diver",
+"rapeseed",
+"daisy",
+"yellow lady's slipper",
+"corn",
+"acorn",
+"rose hip",
+"horse chestnut seed",
+"coral fungus",
+"agaric",
+"gyromitra",
+"stinkhorn mushroom",
+"earth star",
+"hen-of-the-woods",
+"bolete",
+"ear of corn",
+"toilet paper"]

paddle/text.py

+import sys
+import subprocess
+import re
+import paddle
+
+def check_version():
+    try:
+        version = paddle.__version__
+        version_pattern = r"(\d+)\.(\d+)\.(\d+)"
+        match = re.match(version_pattern, version)
+        major, minor, patch_version = map(int, match.groups())
+        return major, minor
+    except ImportError:
+        print("PaddlePaddle is not installed.")
+        sys.exit(1)
+
+major, minor = check_version()
+
+# PaddlePaddle 2.4及以上版本
+if major >= 3 or (major == 2 and minor >= 4):
+    import os
+    import paddle
+    from paddlenlp.transformers import AutoModelForCausalLM, AutoTokenizer
+
+    model = AutoModelForCausalLM.from_pretrained("gpt2")
+    tokenizer = AutoTokenizer.from_pretrained("gpt2")
+
+    prompt = "Once upon a time"
+    input_ids = tokenizer(prompt, return_tensors="pd")["input_ids"]
+
+    output_ids = model.generate(
+        input_ids=input_ids,
+        max_length=50,
+        do_sample=True,
+        top_k=50,
+        top_p=0.95,
+        pad_token_id=tokenizer.pad_token_id,
+        eos_token_id=tokenizer.eos_token_id
+    )
+
+    output_ids = output_ids[0].numpy().flatten()
+    generated_text = tokenizer.decode(output_ids, skip_special_tokens=True)
+    print("Generated Text: ", generated_text)
+
+# PaddlePaddle 2.0到2.3版本
+elif 2 <= major < 3 and 0 <= minor < 4:
+    import paddle
+    from paddlenlp.transformers import BertTokenizer, BertForSequenceClassification
+
+    model_name = "bert-base-uncased"
+    tokenizer = BertTokenizer.from_pretrained(model_name)
+    model = BertForSequenceClassification.from_pretrained(model_name, num_classes=2)
+
+    texts = ["PaddlePaddle is an awesome deep learning framework!", "I don't like the weather today."]
+    input_ids = []
+    token_type_ids = []
+
+    for text in texts:
+        encoded_inputs = tokenizer.encode(text, max_seq_len=128, pad_to_max_seq_len=True)
+        input_ids.append(encoded_inputs['input_ids'])
+        token_type_ids.append(encoded_inputs['token_type_ids'])
+
+    input_ids = paddle.to_tensor(input_ids, dtype='int64')
+    token_type_ids = paddle.to_tensor(token_type_ids, dtype='int64')
+
+    with paddle.no_grad():
+        logits = model(input_ids, token_type_ids=token_type_ids)
+        probs = paddle.nn.functional.softmax(logits, axis=-1)
+        predictions = paddle.argmax(probs, axis=-1)
+
+    for text, pred in zip(texts, predictions.numpy()):
+        label = "Positive" if pred == 1 else "Negative"
+        print(f"Text: {text}\nPrediction: {label}\n")
+
+# PaddlePaddle 2.0以下版本
+else:
+    import paddle.fluid as fluid
+    import numpy as np
+    from paddle.fluid.dygraph import Embedding, Linear
+    from paddle.fluid.dygraph.base import to_variable
+    import paddle.fluid.layers as layers
+
+    class SimpleTextClassifier(fluid.dygraph.Layer):
+        def __init__(self, vocab_size, embedding_dim, hidden_size, num_classes):
+            super(SimpleTextClassifier, self).__init__()
+            self.embedding = Embedding(size=[vocab_size, embedding_dim])
+            self.gru_cell = layers.GRUCell(hidden_size=hidden_size,
+                                           param_attr=fluid.ParamAttr(initializer=fluid.initializer.XavierInitializer()),
+                                           bias_attr=fluid.ParamAttr(initializer=fluid.initializer.Constant(0.0)))
+            self.fc = Linear(hidden_size, num_classes)
+
+        def forward(self, x):
+            x = self.embedding(x)
+            batch_size, seq_len, _ = x.shape
+            hidden = fluid.layers.zeros([batch_size, self.gru_cell.hidden_size], dtype='float32')
+
+            for t in range(seq_len):
+                step_input = x[:, t, :]
+                hidden, _ = self.gru_cell(step_input, hidden)
+
+            logits = self.fc(hidden)
+            return logits
+
+    def preprocess_text(text, vocab, seq_len=20):
+        text_ids = [vocab.get(word, 0) for word in text.split()]
+        text_ids = text_ids[:seq_len] + [0] * (seq_len - len(text_ids))
+        return np.array([text_ids], dtype='int64')
+
+    def infer(text, model, vocab, label_list):
+        with fluid.dygraph.guard():
+            model.eval()
+            text_data = preprocess_text(text, vocab)
+            text_var = to_variable(text_data)
+            logits = model(text_var)
+            prediction = layers.softmax(logits)
+            predicted_class = np.argmax(prediction.numpy())
+            return label_list[predicted_class]
+
+    vocab = {"hello": 1, "world": 2}
+    label_list = ["positive", "negative"]
+    vocab_size = len(vocab) + 1
+    embedding_dim = 128
+    hidden_size = 64
+    num_classes = len(label_list)
+
+    with fluid.dygraph.guard():
+        model = SimpleTextClassifier(vocab_size, embedding_dim, hidden_size, num_classes)
+        model.eval()
+        text = "hello world"
+        predicted_label = infer(text, model, vocab, label_list)
+        print(f"Predicted label: {predicted_label}")
+print("finish")