From 3c06fe00c2a213ab16ef91003085f8086b2edab4 Mon Sep 17 00:00:00 2001
From: rahulgs12 <gsr1998@gmail.com>
Date: Thu, 4 May 2023 12:25:16 -0400
Subject: [PATCH] support cuda #12

---
 Jsonformer_example.ipynb | 3627 +++++++++++++++++++-------------------
 example.ipynb            |  149 +-
 jsonformer/example.py    |    7 +-
 jsonformer/main.py       |   16 +-
 readme.md                |    2 +-
 5 files changed, 1904 insertions(+), 1897 deletions(-)

diff --git a/Jsonformer_example.ipynb b/Jsonformer_example.ipynb
index 32d25cf..9dd1c0a 100644
--- a/Jsonformer_example.ipynb
+++ b/Jsonformer_example.ipynb
@@ -1,1743 +1,11 @@
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@@ -1755,11 +21,10 @@
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+          "output_type": "stream",
           "text": [
             "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
             "Collecting transformers\n",
@@ -1791,6 +56,9 @@
             "Successfully installed huggingface-hub-0.14.1 jsonformer-0.7.0 tokenizers-0.13.3 transformers-4.28.1\n"
           ]
         }
+      ],
+      "source": [
+        "!pip install transformers jsonformer"
       ]
     },
     {
@@ -1863,85 +131,85 @@
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       "outputs": [
         {
-          "output_type": "stream",
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+          "output_type": "stream",
           "text": [
             "Loading model and tokenizer...\n"
           ]
         },
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             "text/plain": [
               "Downloading (…)lve/main/config.json:   0%|          | 0.00/819 [00:00<?, ?B/s]"
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             "text/plain": [
               "Downloading pytorch_model.bin:   0%|          | 0.00/5.68G [00:00<?, ?B/s]"
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+              "model_id": "4a94b28e25d24e26b64fa6505bc57b8a",
+              "version_major": 2,
+              "version_minor": 0
+            },
             "text/plain": [
               "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/2.11M [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "4a94b28e25d24e26b64fa6505bc57b8a"
-            }
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         },
         {
-          "output_type": "display_data",
           "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "39c845eb44494bafb6831988f8f175cc",
+              "version_major": 2,
+              "version_minor": 0
+            },
             "text/plain": [
               "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/228 [00:00<?, ?B/s]"
-            ],
-            "application/vnd.jupyter.widget-view+json": {
-              "version_major": 2,
-              "version_minor": 0,
-              "model_id": "39c845eb44494bafb6831988f8f175cc"
-            }
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         },
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "Loaded model and tokenizer\n"
           ]
@@ -1952,13 +220,38 @@
         "\n",
         "print(\"Loading model and tokenizer...\")\n",
         "model_name = \"databricks/dolly-v2-3b\"\n",
-        "model = AutoModelForCausalLM.from_pretrained(model_name, use_cache=True)\n",
+        "model = AutoModelForCausalLM.from_pretrained(model_name, use_cache=True, device_map=\"auto\")\n",
         "tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True, use_cache=True)\n",
         "print(\"Loaded model and tokenizer\")"
       ]
     },
     {
       "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "8E7zFQ3NO0Yd",
+        "outputId": "b4c201b4-3155-4d21-dc09-aaab8ea6f26a"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Generating...\n",
+            "{\n",
+            "  make: \"Chevrolet\",\n",
+            "  model: \"Malibu\",\n",
+            "  year: 1.0,\n",
+            "  colors: [\n",
+            "    \"blue\"\n",
+            "  ]\n",
+            "}\n"
+          ]
+        }
+      ],
       "source": [
         "from jsonformer.format import highlight_values\n",
         "from jsonformer.main import Jsonformer\n",
@@ -1987,41 +280,1749 @@
         "output = builder()\n",
         "\n",
         "highlight_values(output)\n"
-      ],
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "8E7zFQ3NO0Yd",
-        "outputId": "b4c201b4-3155-4d21-dc09-aaab8ea6f26a"
-      },
-      "execution_count": 3,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Generating...\n",
-            "{\n",
-            "  make: \"Chevrolet\",\n",
-            "  model: \"Malibu\",\n",
-            "  year: 1.0,\n",
-            "  colors: [\n",
-            "    \"blue\"\n",
-            "  ]\n",
-            "}\n"
-          ]
-        }
       ]
     },
     {
       "cell_type": "code",
-      "source": [],
+      "execution_count": 3,
       "metadata": {
         "id": "iQT1jAMMRsWT"
       },
-      "execution_count": 3,
-      "outputs": []
+      "outputs": [],
+      "source": []
     }
-  ]
-}
\ No newline at end of file
+  ],
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+    "accelerator": "GPU",
+    "colab": {
+      "authorship_tag": "ABX9TyMnrvPkgpwg/SWw39ClCVyI",
+      "include_colab_link": true,
+      "machine_shape": "hm",
+      "provenance": []
+    },
+    "gpuClass": "premium",
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
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diff --git a/example.ipynb b/example.ipynb
index 52ccdf8..949056e 100644
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      "text": [
-      "/home/ubuntu/jsonllm/.venv/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "/home/ubuntu/jsonformer/.venv/lib/python3.8/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
       "  from .autonotebook import tqdm as notebook_tqdm\n"
      ]
     },
@@ -26,12 +26,68 @@
     "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
     "\n",
     "print(\"Loading model and tokenizer...\")\n",
-    "model_name = \"databricks/dolly-v2-12b\"\n",
-    "model = AutoModelForCausalLM.from_pretrained(model_name, use_cache=True)\n",
+    "model_name = \"databricks/dolly-v2-3b\"\n",
+    "model = AutoModelForCausalLM.from_pretrained(model_name, use_cache=True, device_map=\"auto\")\n",
     "tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True, use_cache=True)\n",
     "print(\"Loaded model and tokenizer\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Generating...\n",
+      "{\n",
+      "  temperature: \u001b[32m\"22.0\"\u001b[0m,\n",
+      "  humidity: \u001b[32m\"60\"\u001b[0m,\n",
+      "  wind_speed: {\n",
+      "    value: \u001b[32m\"5\"\u001b[0m,\n",
+      "    unit: \u001b[32m\"mph\"\u001b[0m\n",
+      "  }\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "from jsonformer.format import highlight_values\n",
+    "from jsonformer.main import Jsonformer\n",
+    "\n",
+    "weather_schema = {\n",
+    "    \"type\": \"object\",\n",
+    "    \"properties\": {\n",
+    "        \"temperature\": {\"type\": \"string\"},\n",
+    "        \"humidity\": {\n",
+    "            \"type\": \"string\",\n",
+    "        },\n",
+    "        \"wind_speed\": {\n",
+    "            \"type\": \"object\",\n",
+    "            \"properties\": {\n",
+    "                \"value\": {\"type\": \"string\"},\n",
+    "                \"unit\": {\"type\": \"string\"},\n",
+    "            },\n",
+    "        },\n",
+    "    },\n",
+    "}\n",
+    "\n",
+    "builder = Jsonformer(\n",
+    "    model=model,\n",
+    "    tokenizer=tokenizer,\n",
+    "    json_schema=weather_schema,\n",
+    "    prompt=\"generate the weather\",\n",
+    "    device=\"cuda\",\n",
+    ")\n",
+    "\n",
+    "print(\"Generating...\")\n",
+    "output = builder()\n",
+    "\n",
+    "highlight_values(output)\n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
@@ -43,75 +99,11 @@
      "text": [
       "Generating...\n",
       "{\n",
-      "  temperature: \u001b[32m2.2225\u001b[0m,\n",
-      "  humidity: \u001b[32m1.0\u001b[0m,\n",
-      "  wind_speed: {\n",
-      "    value: \u001b[32m0.0\u001b[0m,\n",
-      "    unit: \u001b[32m\"value\"\u001b[0m\n",
-      "  }\n",
-      "}\n"
-     ]
-    }
-   ],
-   "source": [
-    "from jsonformer.format import highlight_values\n",
-    "from jsonformer.main import Jsonformer\n",
-    "\n",
-    "weather_schema = {\n",
-    "    \"type\": \"object\",\n",
-    "    \"properties\": {\n",
-    "        \"temperature\": {\"type\": \"number\"},\n",
-    "        \"humidity\": {\n",
-    "            \"type\": \"number\",\n",
-    "        },\n",
-    "        \"wind_speed\": {\n",
-    "            \"type\": \"object\",\n",
-    "            \"properties\": {\n",
-    "                \"value\": {\"type\": \"number\"},\n",
-    "                \"unit\": {\"type\": \"string\"},\n",
-    "            },\n",
-    "        },\n",
-    "    },\n",
-    "}\n",
-    "\n",
-    "builder = Jsonformer(\n",
-    "    model=model,\n",
-    "    tokenizer=tokenizer,\n",
-    "    json_schema=weather_schema,\n",
-    "    prompt=\"generate the weather\",\n",
-    ")\n",
-    "\n",
-    "print(\"Generating...\")\n",
-    "output = builder()\n",
-    "\n",
-    "highlight_values(output)\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Generating...\n",
-      "{\n",
-      "  make: \u001b[32m\"Ford\"\u001b[0m,\n",
-      "  model: \u001b[32m\"Mustang\"\u001b[0m,\n",
-      "  year: \u001b[32m10.0\u001b[0m,\n",
+      "  make: \u001b[32m\"audi\"\u001b[0m,\n",
+      "  model: \u001b[32m\"model a4\"\u001b[0m,\n",
+      "  year: \u001b[32m1.0\u001b[0m,\n",
       "  colors: [\n",
-      "    \u001b[32m\"red\"\u001b[0m,\n",
-      "    \u001b[32m\"white\"\u001b[0m,\n",
-      "    \u001b[32m\"blue\"\u001b[0m,\n",
-      "    \u001b[32m\"black\"\u001b[0m,\n",
-      "    \u001b[32m\"yellow\"\u001b[0m,\n",
-      "    \u001b[32m\"orange\"\u001b[0m,\n",
-      "    \u001b[32m\"green\"\u001b[0m,\n",
-      "    \u001b[32m\"pink\"\u001b[0m,\n",
-      "    \u001b[32m\"purple\"\u001b[0m,\n",
-      "    \u001b[32m\"violet\"\u001b[0m\n",
+      "    \u001b[32m\"blue\"\u001b[0m\n",
       "  ]\n",
       "}\n"
      ]
@@ -123,11 +115,12 @@
     "    \"properties\": {\n",
     "        \"make\": {\"type\": \"string\"},\n",
     "        \"model\": {\"type\": \"string\"},\n",
-    "        \"year\": {\"type\": \"number\"},\n",
+    "        \"year\": {\"type\": \"string\"},\n",
     "        \"colors\": {\n",
     "            \"type\": \"array\",\n",
     "            \"items\": {\"type\": \"string\"},\n",
-    "        }\n",
+    "        },\n",
+    "        \"shouldUseTurnSignal\": {\"type\": \"boolean\"},\n",
     "    },\n",
     "}\n",
     "\n",
@@ -136,6 +129,7 @@
     "    tokenizer=tokenizer,\n",
     "    json_schema=car,\n",
     "    prompt=\"generate an example car\",\n",
+    "    device=\"cuda\",\n",
     ")\n",
     "\n",
     "print(\"Generating...\")\n",
@@ -143,6 +137,13 @@
     "\n",
     "highlight_values(output)\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -161,7 +162,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.8.10"
   },
   "orig_nbformat": 4
  },
diff --git a/jsonformer/example.py b/jsonformer/example.py
index 99c2f79..937ea5f 100644
--- a/jsonformer/example.py
+++ b/jsonformer/example.py
@@ -6,7 +6,6 @@ from transformers import (
 )
 
 
-
 weather_schema = {
     "type": "object",
     "properties": {
@@ -26,7 +25,10 @@ weather_schema = {
 
 print("Loading model and tokenizer...")
 model_name = "databricks/dolly-v2-12b"
-model = AutoModelForCausalLM.from_pretrained(model_name, use_cache=True)
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_name, use_cache=True, device_map="auto"
+)
 tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True, use_cache=True)
 print("Loaded model and tokenizer")
 
@@ -37,6 +39,7 @@ builder = Jsonformer(
     json_schema=weather_schema,
     prompt="generate the weather",
     debug=True,
+    device="cuda",
 )
 
 print("Generating...")
diff --git a/jsonformer/main.py b/jsonformer/main.py
index 7272393..e6a7569 100644
--- a/jsonformer/main.py
+++ b/jsonformer/main.py
@@ -16,6 +16,8 @@ class Jsonformer:
         tokenizer: PreTrainedTokenizer,
         json_schema: Dict[str, Any],
         prompt: str,
+        *,
+        device: str,
         debug: bool = False,
         max_array_length: int = 10,
         max_number_tokens: int = 6,
@@ -37,6 +39,7 @@ class Jsonformer:
         self.max_number_tokens = max_number_tokens
         self.temperature = temperature
         self.max_string_token_length = max_string_token_length
+        self.device = device
 
     def debug(self, *args, **kwargs):
         if self.debug_on:
@@ -46,7 +49,7 @@ class Jsonformer:
         prompt = self.get_prompt()
         self.debug("[generate_number] prompt", prompt)
         response = self.model.generate(
-            self.tokenizer.encode(prompt, return_tensors="pt"),
+            self.tokenizer.encode(prompt, return_tensors="pt").to(self.model.device),
             max_new_tokens=self.max_number_tokens,
             num_return_sequences=1,
             logits_processor=[self.number_logit_processor],
@@ -70,7 +73,7 @@ class Jsonformer:
         self.debug("[generate_boolean] prompt", prompt)
 
         input_tensor = self.tokenizer.encode(prompt, return_tensors="pt")
-        output = self.model.forward(input_tensor)
+        output = self.model.forward(input_tensor.to(self.model.device))
         logits = output.logits[0, -1]
 
         true_token_id = self.tokenizer.convert_tokens_to_ids("true")
@@ -91,7 +94,7 @@ class Jsonformer:
         prompt = self.get_prompt()
         self.debug("[generate_string] prompt", prompt)
         response = self.model.generate(
-            self.tokenizer.encode(prompt, return_tensors="pt"),
+            self.tokenizer.encode(prompt, return_tensors="pt").to(self.model.device),
             max_new_tokens=self.max_string_token_length,
             num_return_sequences=1,
             temperature=self.temperature,
@@ -118,7 +121,7 @@ class Jsonformer:
         self,
         schema: Dict[str, Any],
         obj: Union[Dict[str, Any], List[Any]],
-        key: str | None = None,
+        key: Union[str, None] = None,
     ) -> Any:
         schema_type = schema["type"]
         if schema_type == "number":
@@ -162,14 +165,14 @@ class Jsonformer:
             input_prompt = self.get_prompt()
             obj.pop()
             input_tensor = self.tokenizer.encode(input_prompt, return_tensors="pt")
-            output = self.model.forward(input_tensor)
+            output = self.model.forward(input_tensor.to(self.model.device))
             logits = output.logits[0, -1]
 
             close_bracket_token_id = self.tokenizer.convert_tokens_to_ids("]")
             comma_token_id = self.tokenizer.convert_tokens_to_ids(", ")
             close_bracket_logits = logits[close_bracket_token_id]
             comma_logits = logits[comma_token_id]
-        
+
             if close_bracket_logits > comma_logits:
                 break
 
@@ -194,7 +197,6 @@ class Jsonformer:
 
     def __call__(self) -> Dict[str, Any]:
         self.value = {}
-
         generated_data = self.generate_object(
             self.json_schema["properties"], self.value
         )
diff --git a/readme.md b/readme.md
index 2771fdf..4d60250 100644
--- a/readme.md
+++ b/readme.md
@@ -47,7 +47,7 @@ json_schema = {
 }
 
 prompt = "Generate a person's information based on the following schema:"
-jsonformer = Jsonformer(model, tokenizer, json_schema, prompt)
+jsonformer = Jsonformer(model, tokenizer, json_schema, prompt, device="cuda")
 generated_data = jsonformer()
 
 print(generated_data)