[pull] master from tensorflow:master

tensorflow/core/BUILD

@@ -1565,7 +1565,6 @@ cc_library(
         "@xla//xla/service:hlo_proto_cc_impl",
         "@xla//xla/service:metrics_proto_cc_impl",
         "@xla//xla/service:buffer_assignment_proto_cc_impl",
-        "@xla//xla/service/memory_space_assignment:memory_space_assignment_proto_cc_impl",
         "@xla//xla/service/gpu:backend_configs_cc_impl",
         "@xla//xla/service/gpu/model:hlo_op_profile_proto_cc_impl",
         "@xla//xla/stream_executor:device_description_proto_cc_impl",

tensorflow/core/kernels/ragged_cross_op.cc

@@ -410,6 +410,13 @@ class RaggedCrossOp : public OpKernel {
         return absl::InvalidArgumentError(
             "tf.ragged.cross only supports inputs with rank=2.");
       }
+      if (sparse_indices_list[i].shape().dim_size(0) !=
+          sparse_values_list[i].shape().dim_size(0)) {
+        return absl::InvalidArgumentError(absl::StrCat(
+            "Expected size of values to be ",
+            sparse_indices_list[i].shape().dim_size(0), " got ",
+            sparse_values_list[i].shape().dim_size(0), " at position ", i));
+      }
     }
     for (int i = 0; i < dense_list.size(); ++i) {
       if (!TensorShapeUtils::IsMatrix(dense_list[i].shape())) {

tensorflow/dtensor/python/d_random.py

@@ -105,7 +105,7 @@ def _old_tf_random_stateless_uniform(
   with ops.name_scope(
       name, "stateless_random_uniform", [shape, seed, minval, maxval]
   ) as name:
-    seed = ops.convert_to_tensor(seed, dtype_hint=dtypes.int32, name="seed")
+    seed = ops.convert_to_tensor(seed, dtype=dtypes.int32, name="seed")
 
     if dtype.is_integer and minval is None and maxval is None:
       result = api.call_with_layout(
@@ -267,7 +267,7 @@ def stateless_split(seed, num=2, mesh=None):
 
 
 def _get_noise_shape(x, noise_shape):
-  """Noisve shape util copied from tf nn_ops."""
+  """Noise shape util copied from tf nn_ops."""
   # If noise_shape is none return immediately.
   if noise_shape is None:
     return array_ops.shape(x)

tensorflow/lite/delegates/flex/kernel.cc

@@ -235,7 +235,7 @@ class OpNode {
   absl::Status InitializeNodeDef(const void* custom_initial_data,
                                  int custom_initial_data_size) {
     if (!custom_initial_data) {
-      return tensorflow::errors::Internal(
+      return absl::InternalError(
           "Cannot convert empty data into a valid NodeDef");
     }
     // The flexbuffer contains a vector where the first elements is the
@@ -249,8 +249,7 @@ class OpNode {
     name_ = v[0].AsString().str();
     if (!nodedef_.ParseFromString(v[1].AsString().str())) {
       nodedef_.Clear();
-      return tensorflow::errors::Internal(
-          "Failed to parse data into a valid NodeDef");
+      return absl::InternalError("Failed to parse data into a valid NodeDef");
     }
 
     // Fill NodeDef with defaults if it's a valid op.
@@ -306,8 +305,8 @@ class OpNode {
         // Lite native buffer, or could be produced by a separater subgraph). We
         // need to fetch it from the delegate's buffer_map.
         if (!buffer_map->HasTensor(input_index)) {
-          return tensorflow::errors::Internal(
-              "Cannot read from invalid tensor index ", input_index);
+          return absl::InternalError(absl::StrCat(
+              "Cannot read from invalid tensor index ", input_index));
         }
         run_state->input_tf_tensors[i] = buffer_map->GetTensor(input_index);
       } else {

tensorflow/lite/delegates/ynnpack/BUILD

@@ -107,7 +107,9 @@ cc_test(
         "//tensorflow/lite/c:common",
         "//tensorflow/lite/kernels:test_util",
         "//tensorflow/lite/schema:schema_fbs",
+        "//tensorflow/lite/types:half",
         "@com_google_googletest//:gtest_main",
+        "@eigen_archive//:eigen3",
         "@flatbuffers//:runtime_cc",
     ],
 )
@@ -124,6 +126,7 @@ cc_binary(
         "//tensorflow/lite/c:common",
         "//tensorflow/lite/kernels:test_util",
         "//tensorflow/lite/schema:schema_fbs",
+        "@com_google_absl//absl/algorithm:container",
         "@com_google_benchmark//:benchmark_main",
         "@flatbuffers//:runtime_cc",
     ],