ci: Torch nightly version upgrade to 2.4.0 (#2704)

Author: gs-olive

README.md

@@ -116,7 +116,7 @@ torch.jit.save(trt_ts_module, "trt_torchscript_module.ts") # save the TRT embedd
 These are the following dependencies used to verify the testcases. Torch-TensorRT can work with other versions, but the tests are not guaranteed to pass.
 
 - Bazel 5.2.0
-- Libtorch 2.3.0.dev (latest nightly) (built with CUDA 12.1)
+- Libtorch 2.4.0.dev (latest nightly) (built with CUDA 12.1)
 - CUDA 12.1
 - cuDNN 8.9.5
 - TensorRT 8.6.1

py/requirements.txt

@@ -2,7 +2,7 @@ numpy
 packaging
 pybind11==2.6.2
 --extra-index-url https://download.pytorch.org/whl/nightly/cu121
-torch>=2.3.0.dev,<2.4.0
+torch>=2.4.0.dev,<2.5.0
 torchvision>=0.18.0.dev,<0.19.0
 --extra-index-url https://pypi.ngc.nvidia.com
 tensorrt==8.6.1

pyproject.toml

@@ -9,7 +9,7 @@ requires = [
     "typing-extensions>=4.7.0",
     "future>=0.18.3",
     "tensorrt>=8.6,<8.7",
-    "torch >=2.3.0.dev,<2.4.0",
+    "torch >=2.4.0.dev,<2.5.0",
     "pybind11==2.6.2",
     "numpy",
 ]
@@ -41,7 +41,7 @@ readme = {file = "py/README.md", content-type = "text/markdown"}
 requires-python = ">=3.8"
 keywords = ["pytorch", "torch", "tensorrt", "trt", "ai", "artificial intelligence", "ml", "machine learning", "dl", "deep learning", "compiler", "dynamo", "torchscript", "inference"]
 dependencies = [
-    "torch >=2.3.0.dev,<2.4.0",
+    "torch >=2.4.0.dev,<2.5.0",
     "tensorrt>=8.6,<8.7",
     "packaging>=23",
     "numpy",