2024-11-12 nightly release (cb9fdbf)

Author: pytorchbot

docs/source/datasets.rst

@@ -27,6 +27,15 @@ All the datasets have almost similar API. They all have two common arguments:
 ``transform`` and  ``target_transform`` to transform the input and target respectively.
 You can also create your own datasets using the provided :ref:`base classes <base_classes_datasets>`.
 
+.. warning::
+
+    When a dataset object is created with ``download=True``, the files are first
+    downloaded and extracted in the root directory. This download logic is not
+    multi-process safe, so it may lead to conflicts / race conditions if it is
+    run within a distributed setting. In distributed mode, we recommend creating
+    a dummy dataset object to trigger the download logic *before* setting up
+    distributed mode.
+
 Image classification
 ~~~~~~~~~~~~~~~~~~~~
 

torchvision/csrc/ops/mps/mps_kernels.h

@@ -5,7 +5,7 @@ namespace ops {
 
 namespace mps {
 
-static const char* METAL_VISION = R"VISION_METAL(
+static at::native::mps::MetalShaderLibrary lib(R"VISION_METAL(
 
 #include <metal_atomic>
 #include <metal_stdlib>
@@ -26,46 +26,15 @@ inline T ceil_div(T n, T m) {
   return (n + m - 1) / m;
 }
 
-template <typename T>
-inline void atomic_add_float( device T* data_ptr, const T val)
+inline void atomic_add_float(device float* data_ptr, const float val)
 {
-#if __METAL_VERSION__ >= 300
-  // atomic_float is supported in Metal 3 (macOS Ventura) onward.
-  device atomic_fetch_add_explicit((device atomic_float*) data_ptr, val, memory_order_relaxed);
-#else
-  // Custom atomic addition implementation
-  // https://github.com/ShoYamanishi/AppleNumericalComputing/blob/053f06c1f5a831095c4bcc29aaf11366fce5231e/03_dot/metal/dot.metal#L447-L472
-  // https://forums.developer.nvidia.com/t/atomicadd-float-float-atomicmul-float-float/14639
-  // https://on-demand.gputechconf.com/gtc/2013/presentations/S3101-Atomic-Memory-Operations.pdf (See the last slide)
-  
-  // Create an atomic uint pointer for atomic transaction.
-  device atomic_uint* atom_var = (device atomic_uint*)data_ptr;
-  // Create necessary storage.
-  uint  fetched_uint,  assigning_uint;
-  T fetched_float, assigning_float;
-
-  // Replace the value in atom_var with 0 and return the previous value in atom_var.
-  fetched_uint = atomic_exchange_explicit( atom_var, 0 /*desired*/, memory_order_relaxed);
-  // Read out the previous value as float.
-  fetched_float = *( (thread T*) &fetched_uint );
-
-  // Do addition and represent the addition result in uint for atomic transaction.
-  assigning_float = fetched_float + val;
-  assigning_uint =  *((thread uint*) &assigning_float);
-
-  // atom_var should be 0 now, try to assign the addition result back to the atom_var (data_ptr).
-  while ((fetched_uint = atomic_exchange_explicit( atom_var, assigning_uint /*desired*/, memory_order_relaxed)) != 0)  {
-    // If atom_var was not 0, i.e. fetched_uint != 0, it means that the data has been modified by other threads.
-    // Try to assign 0 and get the previously assigned addition result.
-    uint fetched_uint_again = atomic_exchange_explicit(atom_var, 0 /*desired*/, memory_order_relaxed);
-    T fetched_float_again = *( (thread T*) &fetched_uint_again );
-    // Re-add again
-    fetched_float = *((thread T*) &(fetched_uint));
-    // Previously assigned addition result + addition result from other threads.
-    assigning_float = fetched_float_again + fetched_float;
-    assigning_uint =  *( (thread uint*) &assigning_float);
-  }
-#endif
+  atomic_fetch_add_explicit((device atomic_float*) data_ptr, val, memory_order_relaxed);
+}
+
+
+inline void atomic_add_float(device half* data_ptr, const half val)
+{
+  atomic_fetch_add_explicit((device atomic_float*) data_ptr, static_cast<float>(val), memory_order_relaxed);
 }
 
 template <typename T, typename integer_t>
@@ -1061,40 +1030,12 @@ REGISTER_PS_ROI_POOL_OP(half, int64_t);
 REGISTER_PS_ROI_POOL_BACKWARD_OP(float, int64_t);
 REGISTER_PS_ROI_POOL_BACKWARD_OP(half, int64_t);
 
-)VISION_METAL";
-
-static id<MTLLibrary> compileVisionOpsLibrary(id<MTLDevice> device) {
-  static id<MTLLibrary> visionLibrary = nil;
-  if (visionLibrary) {
-    return visionLibrary;
-  }
-
-  NSError* error = nil;
-  MTLCompileOptions* options = [[MTLCompileOptions new] autorelease];
-  [options setLanguageVersion:MTLLanguageVersion2_3];
-  visionLibrary = [device newLibraryWithSource:[NSString stringWithCString:METAL_VISION encoding:NSASCIIStringEncoding]
-                                       options:options
-                                         error:&error];
-  TORCH_CHECK(visionLibrary, "Failed to create metal vision library, error: ", [[error description] UTF8String]);
-  return visionLibrary;
-}
-
-static id<MTLComputePipelineState> visionPipelineState(id<MTLDevice> device, const std::string& kernel) {
-  static std::unordered_map<std::string, id<MTLComputePipelineState>> psoCache;
-  id<MTLComputePipelineState> pso = psoCache[kernel];
-  if (pso) {
-    return pso;
-  }
-
-  NSError* error = nil;
-  id<MTLLibrary> visionLib = compileVisionOpsLibrary(device);
-  id<MTLFunction> visionFunc = [visionLib newFunctionWithName:[NSString stringWithUTF8String:kernel.c_str()]];
-  TORCH_CHECK(visionFunc, "Failed to create function state object for: ", kernel);
-  pso = [device newComputePipelineStateWithFunction:visionFunc error:&error];
-  TORCH_CHECK(pso, "Failed to created pipeline state object, error: ", [[error description] UTF8String]);
+)VISION_METAL");
 
-  psoCache[kernel] = pso;
-  return pso;
+static id<MTLComputePipelineState> visionPipelineState(
+    id<MTLDevice> device,
+    const std::string& kernel) {
+  return lib.getPipelineStateForFunc(kernel);
 }
 
 } // namespace mps

torchvision/csrc/ops/mps/ps_roi_pool_kernel.mm

@@ -123,7 +123,6 @@
 
   float spatial_scale_f = static_cast<float>(spatial_scale);
 
-  auto num_rois = rois.size(0);
   auto grad_input = at::zeros({batch_size, channels, height, width}, grad.options());
 
   if (grad.numel() == 0) {