Read from a sharded checkpoint in parallel with multiple threads.

PiperOrigin-RevId: 313506462
Change-Id: I1cef16cdaa9e03fd3161727614007429221089e0

tensorflow/core/util/tensor_bundle/tensor_bundle.cc

@@ -34,7 +34,6 @@ limitations under the License.
 #include "tensorflow/core/lib/bfloat16/bfloat16.h"
 #include "tensorflow/core/lib/core/coding.h"
 #include "tensorflow/core/lib/core/errors.h"
-#include "tensorflow/core/lib/gtl/cleanup.h"
 #include "tensorflow/core/lib/gtl/map_util.h"
 #include "tensorflow/core/lib/hash/crc32c.h"
 #include "tensorflow/core/lib/io/path.h"
@@ -42,8 +41,6 @@ limitations under the License.
 #include "tensorflow/core/lib/random/random.h"
 #include "tensorflow/core/lib/strings/str_util.h"
 #include "tensorflow/core/lib/strings/stringprintf.h"
-#include "tensorflow/core/platform/blocking_counter.h"
-#include "tensorflow/core/platform/status.h"
 #include "tensorflow/core/util/env_var.h"
 #include "tensorflow/core/util/saved_tensor_slice_util.h"
 #include "tensorflow/core/util/tensor_bundle/byte_swap.h"
@@ -1024,23 +1021,10 @@ Status BundleReader::GetSliceValue(StringPiece full_tensor_key,
         " to restore in slice_spec: ", slice_spec.DebugString());
   }
 
-  BlockingCounter counter(static_cast<int>(details.size()));
-  auto runner = [this, &details](std::function<void()> fn) {
-    if (details.size() > 1) {
-      // If there are multiple slices to read, perform the read in parallel
-      // using multiple threads.
-      env_->SchedClosure(fn);
-    } else {
-      fn();
-    }
-  };
-
-  for (const auto& slice_tag_pair : details) {
-    runner([this, &slice_spec, &full_shape, &slice_tag_pair, &full_tensor_entry,
-            &full_tensor_key_string, &counter, val]() {
   // The union of the slices in "details" covers "slice_spec".  Performs the
   // copies from each.
   BundleEntryProto stored_slice_entry = full_tensor_entry;
+  for (const auto& slice_tag_pair : details) {
     // Seeks for the stored slice.
     const TensorSlice& stored_slice = slice_tag_pair.first;
 
@@ -1050,25 +1034,20 @@ Status BundleReader::GetSliceValue(StringPiece full_tensor_key,
       const string encoded_stored_slice_name =
           checkpoint::EncodeTensorNameSlice(full_tensor_key_string,
                                             stored_slice);
-        mutex_lock l(mu_);
-        // `GetBundleEntryProto` will access `iter_`, so protecting it with a
-        // mutex lock.
       status_ =
           GetBundleEntryProto(encoded_stored_slice_name, &stored_slice_entry);
-        if (!status_.ok()) return;
+      if (!status_.ok()) return status_;
     }
 
-      auto cleanup = gtl::MakeCleanup([&counter] { counter.DecrementCount(); });
-
-      // TODO(zongheng): should we take an OpKernelContext, so that we can
-      // call allocate_temp()?  Note that without major refactorings to
-      // Saver, it's hard for the caller of the tensor bundle module to
-      // allocate these precisely-shaped scratch storage.
+    // TODO(zongheng): should we take an OpKernelContext, so that we can call
+    // allocate_temp()?  Note that without major refactorings to Saver, it's
+    // hard for the caller of the tensor bundle module to allocate these
+    // precisely-shaped scratch storage.
 
     // Optimization for the common case: the stored slice can be directly
-      // copied to the destination without additional slicing. This is true
-      // when either the slices are equal or when they are both full slices
-      // having the same shape.
+    // copied to the destination without additional slicing. This is true when
+    // either the slices are equal or when they are both full slices having the
+    // same shape.
     TensorShape stored_slice_shape(stored_slice_entry.shape());
     if (stored_slice == slice_spec ||
         (stored_slice_shape == val->shape() &&
@@ -1078,18 +1057,14 @@ Status BundleReader::GetSliceValue(StringPiece full_tensor_key,
                  "pre-allocated buffer; spec: "
               << slice_spec.DebugString();
       status_ = GetValue(stored_slice_entry, val);
-        return;
+      return status_;
     }
 
-      Tensor stored_slice_tensor(stored_slice_entry.dtype(),
-                                 stored_slice_shape);
+    Tensor stored_slice_tensor(stored_slice_entry.dtype(), stored_slice_shape);
     status_ = GetValue(stored_slice_entry, &stored_slice_tensor);
-      if (!status_.ok()) return;
+    if (!status_.ok()) return status_;
 
     // Copies the intersection over.
-      mutex_lock l(mu_);
-      // `CopyDataFromTensorSliceToTensorSlice` will write to `val`, so
-      // protecting it with a mutex lock.
     const DataType common_dtype = full_tensor_entry.dtype();
     switch (common_dtype) {
 #define HANDLE_COPY(T)                                                 \
@@ -1098,6 +1073,7 @@ Status BundleReader::GetSliceValue(StringPiece full_tensor_key,
         full_shape, stored_slice, slice_spec,                          \
         stored_slice_tensor.flat<T>().data(), val->flat<T>().data())); \
     break;
+
       HANDLE_COPY(float)
       HANDLE_COPY(double)
       HANDLE_COPY(int32)
@@ -1113,17 +1089,11 @@ Status BundleReader::GetSliceValue(StringPiece full_tensor_key,
       HANDLE_COPY(qint8)
       HANDLE_COPY(bfloat16)
       default:
-          status_ = errors::InvalidArgument(
-              "Dtype ", DataTypeString(common_dtype), " not supported.");
-          if (!status_.ok()) return;
+        return errors::InvalidArgument("Dtype ", DataTypeString(common_dtype),
+                                       " not supported.");
     }
 #undef HANDLE_COPY
-    });
   }
-
-  counter.Wait();
-  TF_RETURN_IF_ERROR(status_);
-
   return Status::OK();
 }
 

tensorflow/core/util/tensor_bundle/tensor_bundle.h

@@ -306,9 +306,6 @@ class BundleReader {
   // differs from that of the current system's processor architecture.
   bool need_to_swap_bytes_;
 
-  // Protect internal states when accessing from multiple threads.
-  mutable mutex mu_;
-
   friend class TensorBundleAlignmentTest;  // For testing data alignment.
 
   TF_DISALLOW_COPY_AND_ASSIGN(BundleReader);