From b50a327a043057103e995ce7d472a4804f295a0f Mon Sep 17 00:00:00 2001
From: Glenn Jocher <glenn.jocher@ultralytics.com>
Date: Wed, 19 Feb 2025 23:01:56 +0800
Subject: [PATCH] Allow missing `thop` package (#19314)

Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
---
 ultralytics/nn/tasks.py          |  6 +++++-
 ultralytics/utils/torch_utils.py | 11 +++++++++--
 2 files changed, 14 insertions(+), 3 deletions(-)

diff --git a/ultralytics/nn/tasks.py b/ultralytics/nn/tasks.py
index 4ed8d7da39..4d845ae9c5 100644
--- a/ultralytics/nn/tasks.py
+++ b/ultralytics/nn/tasks.py
@@ -7,7 +7,6 @@ import types
 from copy import deepcopy
 from pathlib import Path
 
-import thop
 import torch
 
 from ultralytics.nn.modules import (
@@ -86,6 +85,11 @@ from ultralytics.utils.torch_utils import (
     time_sync,
 )
 
+try:
+    import thop
+except ImportError:
+    thop = None  # conda support without 'ultralytics-thop' installed
+
 
 class BaseModel(torch.nn.Module):
     """The BaseModel class serves as a base class for all the models in the Ultralytics YOLO family."""
diff --git a/ultralytics/utils/torch_utils.py b/ultralytics/utils/torch_utils.py
index a589b7d640..83eb303725 100644
--- a/ultralytics/utils/torch_utils.py
+++ b/ultralytics/utils/torch_utils.py
@@ -12,7 +12,6 @@ from pathlib import Path
 from typing import Union
 
 import numpy as np
-import thop
 import torch
 import torch.distributed as dist
 import torch.nn as nn
@@ -31,6 +30,11 @@ from ultralytics.utils import (
 )
 from ultralytics.utils.checks import check_version
 
+try:
+    import thop
+except ImportError:
+    thop = None  # conda support without 'ultralytics-thop' installed
+
 # Version checks (all default to version>=min_version)
 TORCH_1_9 = check_version(torch.__version__, "1.9.0")
 TORCH_1_13 = check_version(torch.__version__, "1.13.0")
@@ -370,6 +374,9 @@ def model_info_for_loggers(trainer):
 
 def get_flops(model, imgsz=640):
     """Return a YOLO model's FLOPs."""
+    if not thop:
+        return 0.0  # if not installed return 0.0 GFLOPs
+
     try:
         model = de_parallel(model)
         p = next(model.parameters())
@@ -681,7 +688,7 @@ def profile(input, ops, n=10, device=None, max_num_obj=0):
             m = m.half() if hasattr(m, "half") and isinstance(x, torch.Tensor) and x.dtype is torch.float16 else m
             tf, tb, t = 0, 0, [0, 0, 0]  # dt forward, backward
             try:
-                flops = thop.profile(deepcopy(m), inputs=[x], verbose=False)[0] / 1e9 * 2  # GFLOPs
+                flops = thop.profile(deepcopy(m), inputs=[x], verbose=False)[0] / 1e9 * 2 if thop else 0  # GFLOPs
             except Exception:
                 flops = 0