Merge branch 'main' into dynamo_refactor

Author: peri044

.circleci/config.yml

@@ -252,10 +252,10 @@ commands:
     parameters:
       torch-build:
         type: string
-        default: "2.1.0.dev20230619+cu121"
+        default: "2.1.0.dev20230703+cu121"
       torchvision-build:
         type: string
-        default: "0.16.0.dev20230619+cu121"
+        default: "0.16.0.dev20230703+cu121"
       torch-build-index:
         type: string
         default: "https://download.pytorch.org/whl/nightly/cu121"
@@ -1338,10 +1338,10 @@ parameters:
   # Nightly platform config
   torch-build:
     type: string
-    default: "2.1.0.dev20230619+cu121"
+    default: "2.1.0.dev20230703+cu121"
   torchvision-build:
     type: string
-    default: "0.16.0.dev20230619+cu121"
+    default: "0.16.0.dev20230703+cu121"
   torch-build-index:
     type: string
     default: "https://download.pytorch.org/whl/nightly/cu121"

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 2.1.0.dev20230619 (built with CUDA 12.1)
+- Libtorch 2.1.0.dev20230703 (built with CUDA 12.1)
 - CUDA 12.1
 - cuDNN 8.8.1
 - TensorRT 8.6.1

WORKSPACE

@@ -51,17 +51,17 @@ new_local_repository(
 http_archive(
     name = "libtorch",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "5ba55259b65e071346a2b547b8d1378595f1467a39aaa923fecb09f134f1bcba",
+    sha256 = "1ae8366aaf7af7f68f142ba644fe26c837c6fa8347ec6bd9ce605ac60e7f7e5e",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-cxx11-abi-shared-with-deps-2.1.0.dev20230619%2Bcu121.zip"],
+    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-cxx11-abi-shared-with-deps-2.1.0.dev20230703%2Bcu121.zip"],
 )
 
 http_archive(
     name = "libtorch_pre_cxx11_abi",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "8f6661bfc11597e77400e9e36cc8dd8e5e385ba82361d630d9ccede8518d7c7e",
+    sha256 = "9add4832f4da9223866d85810820b816ab3319d5a227066101eeb6cbb76adb4b",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-shared-with-deps-2.1.0.dev20230619%2Bcu121.zip"],
+    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-shared-with-deps-2.1.0.dev20230703%2Bcu121.zip"],
 )
 
 # Download these tarballs manually from the NVIDIA website

py/requirements.txt

@@ -2,7 +2,7 @@ numpy
 packaging
 pybind11==2.6.2
 --extra-index-url https://download.pytorch.org/whl/nightly/cu121
-torch==2.1.0.dev20230619+cu121
-torchvision==0.16.0.dev20230619+cu121
+torch==2.1.0.dev20230703+cu121
+torchvision==0.16.0.dev20230703+cu121
 --extra-index-url https://pypi.ngc.nvidia.com
 tensorrt==8.6.1

py/torch_tensorrt/dynamo/lowering/_decompositions.py

@@ -27,12 +27,8 @@ def inplace_op(*args, **kwargs):
 replace_inplace_op(aten.addmv_, aten.addmv)
 replace_inplace_op(aten.baddbmm_, aten.baddbmm)
 replace_inplace_op(aten.cumprod_, aten.cumprod)
-replace_inplace_op(aten.fill_, aten.fill)
-replace_inplace_op(aten.gelu_, aten.gelu)
-replace_inplace_op(aten.hardsigmoid_, aten.hardsigmoid)
 replace_inplace_op(aten.index_put_, aten.index_put)
 replace_inplace_op(aten.index_reduce_, aten.index_reduce)
-replace_inplace_op(aten.logit_, aten.logit)
 replace_inplace_op(aten.relu_, aten.relu)
 replace_inplace_op(aten.round_, aten.round)
 replace_inplace_op(aten.scatter_, aten.scatter)

py/torch_tensorrt/fx/test/passes/test_fix_reshape_batch_dim.py

@@ -35,11 +35,11 @@ def forward(self, x, y):
 
         expected_graph = r"""
 graph():
-    %x : [#users=0] = placeholder[target=x]
-    %y : [#users=2] = placeholder[target=y]
-    %size : [#users=1] = call_function[target=torch_tensorrt.fx.tracer.acc_tracer.acc_ops.size](args = (), kwargs = {input: %y})
-    %getitem_1 : [#users=1] = call_function[target=torch_tensorrt.fx.tracer.acc_tracer.acc_ops.getitem](args = (), kwargs = {idx: 0, input: %size})
-    %reshape : [#users=1] = call_function[target=torch_tensorrt.fx.tracer.acc_tracer.acc_ops.reshape](args = (), kwargs = {input: %y, acc_out_ty: ((%getitem_1, -1, 3), None, None, None, None, None, None)})
+    %x : [num_users=0] = placeholder[target=x]
+    %y : [num_users=2] = placeholder[target=y]
+    %size : [num_users=1] = call_function[target=torch_tensorrt.fx.tracer.acc_tracer.acc_ops.size](args = (), kwargs = {input: %y})
+    %getitem_1 : [num_users=1] = call_function[target=torch_tensorrt.fx.tracer.acc_tracer.acc_ops.getitem](args = (), kwargs = {idx: 0, input: %size})
+    %reshape : [num_users=1] = call_function[target=torch_tensorrt.fx.tracer.acc_tracer.acc_ops.reshape](args = (), kwargs = {input: %y, acc_out_ty: ((%getitem_1, -1, 3), None, None, None, None, None, None)})
     return reshape
 """
         assert (

py/torch_tensorrt/fx/test/passes/test_remove_duplicate_output_args.py

@@ -47,11 +47,11 @@ def is_leaf_module(self, m, qn):
         ttop_graph_actual = str(ttop.graph).strip()
         ttop_graph_expected = """
 graph():
-    %x : [#users=1] = placeholder[target=x]
-    %a : [#users=2] = call_module[target=a](args = (%x,), kwargs = {})
-    %getitem : [#users=1] = call_function[target=operator.getitem](args = (%a, 0), kwargs = {})
-    %getitem_1 : [#users=1] = call_function[target=operator.getitem](args = (%a, 0), kwargs = {})
-    %add : [#users=1] = call_function[target=operator.add](args = (%getitem, %getitem_1), kwargs = {})
+    %x : [num_users=1] = placeholder[target=x]
+    %a : [num_users=2] = call_module[target=a](args = (%x,), kwargs = {})
+    %getitem : [num_users=1] = call_function[target=operator.getitem](args = (%a, 0), kwargs = {})
+    %getitem_1 : [num_users=1] = call_function[target=operator.getitem](args = (%a, 0), kwargs = {})
+    %add : [num_users=1] = call_function[target=operator.add](args = (%getitem, %getitem_1), kwargs = {})
     return add
 """.strip()
         assert (
@@ -61,7 +61,7 @@ def is_leaf_module(self, m, qn):
         ttop_a_graph_actual = str(ttop.a.graph).strip()
         ttop_a_graph_expected = """
 graph():
-    %x : [#users=1] = placeholder[target=x]
+    %x : [num_users=1] = placeholder[target=x]
     return (x,)
 """.strip()
         assert (

toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel

@@ -56,17 +56,17 @@ new_local_repository(
 http_archive(
     name = "libtorch",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "5ba55259b65e071346a2b547b8d1378595f1467a39aaa923fecb09f134f1bcba",
+    sha256 = "1ae8366aaf7af7f68f142ba644fe26c837c6fa8347ec6bd9ce605ac60e7f7e5e",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-cxx11-abi-shared-with-deps-2.1.0.dev20230619%2Bcu121.zip"],
+    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-cxx11-abi-shared-with-deps-2.1.0.dev20230703%2Bcu121.zip"],
 )
 
 http_archive(
     name = "libtorch_pre_cxx11_abi",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "8f6661bfc11597e77400e9e36cc8dd8e5e385ba82361d630d9ccede8518d7c7e",
+    sha256 = "9add4832f4da9223866d85810820b816ab3319d5a227066101eeb6cbb76adb4b",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-shared-with-deps-2.1.0.dev20230619%2Bcu121.zip"],
+    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-shared-with-deps-2.1.0.dev20230703%2Bcu121.zip"],
 )
 
 ####################################################################################

toolchains/ci_workspaces/WORKSPACE.x86_64.release.ubuntu

@@ -56,17 +56,17 @@ new_local_repository(
 http_archive(
     name = "libtorch",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "5ba55259b65e071346a2b547b8d1378595f1467a39aaa923fecb09f134f1bcba",
+    sha256 = "1ae8366aaf7af7f68f142ba644fe26c837c6fa8347ec6bd9ce605ac60e7f7e5e",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-cxx11-abi-shared-with-deps-2.1.0.dev20230619%2Bcu121.zip"],
+    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-cxx11-abi-shared-with-deps-2.1.0.dev20230703%2Bcu121.zip"],
 )
 
 http_archive(
     name = "libtorch_pre_cxx11_abi",
     build_file = "@//third_party/libtorch:BUILD",
-    sha256 = "8f6661bfc11597e77400e9e36cc8dd8e5e385ba82361d630d9ccede8518d7c7e",
+    sha256 = "9add4832f4da9223866d85810820b816ab3319d5a227066101eeb6cbb76adb4b",
     strip_prefix = "libtorch",
-    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-shared-with-deps-2.1.0.dev20230619%2Bcu121.zip"],
+    urls = ["https://download.pytorch.org/libtorch/nightly/cu121/libtorch-shared-with-deps-2.1.0.dev20230703%2Bcu121.zip"],
 )
 
 ####################################################################################