update pin (#8677)

WORKSPACE

@@ -46,7 +46,7 @@ new_local_repository(
 
 # To build PyTorch/XLA with OpenXLA to a new revision, update following xla_hash to
 # the openxla git commit hash.
-xla_hash = '6e91ff19dad528ab7d2025a9bb46150618a3bc7d'
+xla_hash = '52d5ccaf00fdbc32956c457eae415c09f56f0208'
 
 http_archive(
     name = "xla",
@@ -57,6 +57,7 @@ http_archive(
     patch_tool = "patch",
     patches = [
         "//openxla_patches:gpu_race_condition.diff",
+        "//openxla_patches:count_down.diff",
     ],
     strip_prefix = "xla-" + xla_hash,
     urls = [

openxla_patches/count_down.diff

@@ -0,0 +1,14 @@
+diff --git a/xla/backends/cpu/runtime/convolution_thunk_internal.h b/xla/backends/cpu/runtime/convolution_thunk_internal.h
+index 84fed6bb78..9835f12e4e 100644
+--- a/xla/backends/cpu/runtime/convolution_thunk_internal.h
++++ b/xla/backends/cpu/runtime/convolution_thunk_internal.h
+@@ -342,7 +342,8 @@ void EigenGenericConv2D(
+         Eigen::Index start = task_index * task_size;
+         Eigen::Index end = std::min(start + task_size, feature_group_count);
+         for (Eigen::Index i = start; i < end; ++i) {
+-          auto on_done = [count_down]() mutable { count_down.CountDown(); };
++          // auto on_done = [count_down]() mutable { count_down.CountDown(); };
++          auto on_done = [count_down]() mutable { const_cast<decltype(count_down)*>(&count_down)->CountDown(); };
+           auto [output, convolved] = convolve_group(i);
+           output.device(device, std::move(on_done)) = convolved;
+         }

setup.py

@@ -66,10 +66,10 @@
 
 USE_NIGHTLY = True  # whether to use nightly or stable libtpu and jax
 
-_date = '20250131'
+_date = '20250210'
 
 # Note: jax/jaxlib 20250115 build will fail. Check https://github.com/pytorch/xla/pull/8621#issuecomment-2616564634 for more details.
-_libtpu_version = '0.0.9'
+_libtpu_version = '0.0.10'
 _jax_version = '0.5.1'
 _jaxlib_version = '0.5.1'
 
@@ -332,9 +332,6 @@ def run(self):
         'tpu': [
             f'libtpu=={_libtpu_version}',
             'tpu-info',
-            # This special version removes `libtpu.so` from any `libtpu-nightly` installations,
-            # since we have migrated to using the `libtpu.so` from the `libtpu` package.
-            "libtpu-nightly==0.1.dev20241010+nightly.cleanup"
         ],
         # pip install torch_xla[pallas] -f https://storage.googleapis.com/jax-releases/jax_nightly_releases.html -f https://storage.googleapis.com/jax-releases/jaxlib_nightly_releases.html
         'pallas': [f'jaxlib=={_jaxlib_version}', f'jax=={_jax_version}'],

test/test_core_aten_ops.py

@@ -993,7 +993,10 @@ def test_aten_convolution_1(self):
         1,
     )
     kwargs = dict()
-    run_export_and_compare(self, torch.ops.aten.convolution, args, kwargs)
+    # With xla pin to 52d5ccaf00fdbc32956c457eae415c09f56f0208
+    # The rtol needs to be raise to 1e-3 on CPU.
+    run_export_and_compare(
+        self, torch.ops.aten.convolution, args, kwargs, rtol=1e-3)
 
   def test_aten_convolution_2(self):
     args = (

torch_xla/csrc/dl_convertor.cpp

@@ -329,7 +329,7 @@ at::Tensor fromDLPack(DLManagedTensor* dlmt) {
       device->client()->CreateViewOfDeviceBuffer(
           static_cast<char*>(dlmt->dl_tensor.data) +
               dlmt->dl_tensor.byte_offset,
-          shape, device, on_delete_callback);
+          shape, *device->default_memory_space(), on_delete_callback);
   XLA_CHECK_OK(pjrt_buffer.status()) << "Failed to create a pjrt buffer.";
   XLA_CHECK(pjrt_buffer.value() != nullptr) << "pjrt buffer is null.";
 

torch_xla/csrc/runtime/BUILD

@@ -165,6 +165,7 @@ cc_library(
         ":tf_logging",
         "@tsl//tsl/platform:stacktrace",
         "@tsl//tsl/platform:statusor",
+        "@tsl//tsl/platform:macros",
     ],
 )
 

torch_xla/csrc/runtime/pjrt_computation_client.cc

@@ -274,7 +274,9 @@ std::vector<ComputationClient::DataPtr> PjRtComputationClient::TransferToDevice(
                           tensor->dimensions(), tensor->byte_strides(),
                           xla::PjRtClient::HostBufferSemantics::
                               kImmutableUntilTransferCompletes,
-                          [tensor]() { /* frees tensor */ }, pjrt_device)
+                          [tensor]() { /* frees tensor */ },
+                          *pjrt_device->default_memory_space(),
+                          /*device_layout=*/nullptr)
                       .value());
 
     ComputationClient::DataPtr data =
@@ -321,7 +323,7 @@ ComputationClient::DataPtr PjRtComputationClient::CopyToDevice(
 
   // Returns error if the buffer is already on `dst_device`.
   absl::StatusOr<std::unique_ptr<xla::PjRtBuffer>> status_or =
-      pjrt_data->buffer->CopyToDevice(dst_device);
+      pjrt_data->buffer->CopyToMemorySpace(*dst_device->default_memory_space());
   if (!status_or.ok()) {
     return data;
   }