avoid random lib usage (#2344)

openvinotoolkit · Sep 2, 2024 · c81e765 · c81e765
1 parent 593da6b
commit c81e765
Show file tree

Hide file tree

Showing 17 changed files with 527 additions and 86 deletions.
diff --git a/notebooks/ct-segmentation-quantize/ct-segmentation-quantize-nncf.ipynb b/notebooks/ct-segmentation-quantize/ct-segmentation-quantize-nncf.ipynb
diff --git a/notebooks/explainable-ai-3-map-interpretation/explainable-ai-3-map-interpretation.ipynb b/notebooks/explainable-ai-3-map-interpretation/explainable-ai-3-map-interpretation.ipynb
@@ -1,6 +1,7 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -62,6 +63,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -93,6 +95,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -107,7 +110,6 @@
    "outputs": [],
    "source": [
     "import os\n",
-    "import random\n",
     "import zipfile\n",
     "from pathlib import Path\n",
     "\n",
@@ -131,6 +133,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -139,6 +142,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -211,12 +215,13 @@
     "print(f\"Number of images to get explanations: {len(img_files)}\")\n",
     "\n",
     "# Get a fewer subset for fast execution\n",
-    "random.seed(42)\n",
-    "img_files = random.sample(img_files, 1)\n",
+    "np.random.seed(42)\n",
+    "img_files = np.random.choice(img_files, 1)\n",
     "print(f\"Run explanations on fewer number of images: {len(img_files)}\")"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -257,6 +262,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -265,6 +271,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -302,6 +309,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -322,6 +330,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -330,6 +339,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -377,6 +387,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -385,6 +396,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -393,6 +405,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -432,6 +445,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -440,6 +454,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -490,6 +505,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -498,6 +514,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -527,6 +544,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -554,6 +572,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -562,6 +581,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -668,6 +688,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -796,6 +817,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -820,6 +842,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -828,6 +851,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -871,6 +895,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -879,6 +904,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -892,6 +918,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -900,6 +927,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -928,6 +956,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -939,6 +968,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -967,13 +997,15 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "`True positive low confidence` basically means that key features are not well available or are transformed. From the saliency maps, we see that the model is paying attention to the whole object, trying to make a decision mostly based on high-level features."
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -1002,6 +1034,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -1021,6 +1054,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -1049,6 +1083,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [

diff --git a/notebooks/florence2/gradio_helper.py b/notebooks/florence2/gradio_helper.py
@@ -1,6 +1,5 @@
 import io
 import copy
-import random
 import requests
 from pathlib import Path
 
@@ -68,8 +67,13 @@ def draw_polygons(image, prediction, fill_mask=False):
     draw = ImageDraw.Draw(image)
     scale = 1
     for polygons, label in zip(prediction["polygons"], prediction["labels"]):
-        color = random.choice(colormap)
-        fill_color = random.choice(colormap) if fill_mask else None
+        color_id = np.random.choice(len(colormap))
+        color = colormap[color_id]
+        if fill_mask:
+            fill_color_id = np.random.choice(len(colormap))
+            fill_color = colormap[fill_color_id]
+        else:
+            fill_color = None
         for _polygon in polygons:
             _polygon = np.array(_polygon).reshape(-1, 2)
             if len(_polygon) < 3:
@@ -96,7 +100,8 @@ def draw_ocr_bboxes(image, prediction):
     draw = ImageDraw.Draw(image)
     bboxes, labels = prediction["quad_boxes"], prediction["labels"]
     for box, label in zip(bboxes, labels):
-        color = random.choice(colormap)
+        color_id = np.random.choice(len(colormap))
+        color = colormap[color_id]
         new_box = (np.array(box) * scale).tolist()
         draw.polygon(new_box, width=3, outline=color)
         draw.text((new_box[0] + 8, new_box[1] + 2), "{}".format(label), align="right", fill=color)

diff --git a/notebooks/flux.1-image-generation/gradio_helper.py b/notebooks/flux.1-image-generation/gradio_helper.py
@@ -1,6 +1,5 @@
 import gradio as gr
 import numpy as np
-import random
 import torch
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -23,7 +22,7 @@
 def make_demo(ov_pipe):
     def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, guidance_scale=0, progress=gr.Progress(track_tqdm=True)):
         if randomize_seed:
-            seed = random.randint(0, MAX_SEED)
+            seed = np.random.randint(0, MAX_SEED)
         generator = torch.Generator().manual_seed(seed)
         image = ov_pipe(
             prompt=prompt, width=width, height=height, num_inference_steps=num_inference_steps, generator=generator, guidance_scale=guidance_scale

diff --git a/notebooks/grounded-segment-anything/grounded-segment-anything.ipynb b/notebooks/grounded-segment-anything/grounded-segment-anything.ipynb
@@ -966,13 +966,12 @@
    "outputs": [],
    "source": [
     "def draw_mask(mask, draw, random_color=False):\n",
-    "    import random\n",
     "\n",
     "    if random_color:\n",
     "        color = (\n",
-    "            random.randint(0, 255),\n",
-    "            random.randint(0, 255),\n",
-    "            random.randint(0, 255),\n",
+    "            np.random.randint(0, 255),\n",
+    "            np.random.randint(0, 255),\n",
+    "            np.random.randint(0, 255),\n",
     "            153,\n",
     "        )\n",
     "    else:\n",

diff --git a/notebooks/instant-id/gradio_helper.py b/notebooks/instant-id/gradio_helper.py
@@ -1,7 +1,6 @@
 from pathlib import Path
 from typing import Callable
 import gradio as gr
-import random
 import numpy as np
 from diffusers.utils import load_image
 from style_template import styles
@@ -32,7 +31,7 @@
 
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
+        seed = np.random.randint(0, MAX_SEED)
     return seed
 
 

diff --git a/notebooks/llava-next-multimodal-chatbot/llava-next-multimodal-chatbot.ipynb b/notebooks/llava-next-multimodal-chatbot/llava-next-multimodal-chatbot.ipynb
@@ -986,7 +986,7 @@
     "        batch_size = input_ids.shape[0]\n",
     "        if not self.stateful:\n",
     "            for input_name in self.key_value_input_names:\n",
-    "                model_inputs = self.modeget_anyres_image_grid_shapel.input(input_name)\n",
+    "                model_inputs = self.model.input(input_name)\n",
     "                shape = model_inputs.get_partial_shape()\n",
     "                shape[0] = batch_size\n",
     "                if shape[2].is_dynamic:\n",