// Calc Grad
    AbstractTensorHandle* matmul_A_output;
    AbstractTensorHandle* matmul_B_output;
    std::string name_grad_A = "MatMul_Grad_A";
    std::string name_grad_B = "MatMul_Grad_B";
    if (!t_a && !t_b) {
      TF_RETURN_IF_ERROR(MatMul(ctx, upstream_grad, B.get(), &matmul_A_output,
                                /*transpose_a = */ false,

              absl::Span<AbstractTensorHandle* const> inputs,
              absl::Span<AbstractTensorHandle*> outputs) -> Status {
        return ops::MatMul(ctx, inputs[0], inputs[1], &outputs[0], transpose_a,
                           transpose_b, "MatMul");
      };
      ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients(
          MatMulModel, BuildGradModel(MatMulModel, registry_),

  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> matmul(
      MatMulOp(context, hcpu, hdevice), TFE_DeleteOp);
  TFE_OpSetDevice(matmul.get(), name, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  TFE_TensorHandle* retval;
  int num_retvals = 1;
  TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());

  TFE_Context* tfe_context_;
};

TEST_F(ShapeInferenceTest, InfersShapesFromInputShapes) {
  TFE_Op* matmul_op;
  matmul_op = TFE_NewOp(tfe_context_, "MatMul", status_);
  CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);

  // Infer shape when everything is known.
  CheckOutputShapes(matmul_op,
                    /*input_shapes*/ {make_shape({3, 2}), make_shape({2, 4})},
                    /*input_tensors*/ {},

  // Build an abstract operation.
  auto* matmul_op = TF_NewAbstractOp(graph_ctx);
  TF_AbstractOpSetOpType(matmul_op, "MatMul", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  TF_AbstractOpSetOpName(matmul_op, "my_matmul", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

 * the License.
 */

package com.google.common.math;

import static com.google.common.truth.Truth.assertThat;
import static com.google.common.truth.Truth.assertWithMessage;
import static java.math.RoundingMode.CEILING;
import static java.math.RoundingMode.DOWN;
import static java.math.RoundingMode.FLOOR;
import static java.math.RoundingMode.HALF_DOWN;
import static java.math.RoundingMode.HALF_EVEN;

import static com.google.common.math.StatsTesting.EMPTY_STATS_ITERABLE;
import static com.google.common.math.StatsTesting.HORIZONTAL_VALUES_PAIRED_STATS;
import static com.google.common.math.StatsTesting.MANY_VALUES;
import static com.google.common.math.StatsTesting.MANY_VALUES_COUNT;
import static com.google.common.math.StatsTesting.MANY_VALUES_PAIRED_STATS;

import static com.google.common.math.StatsTesting.EMPTY_STATS_ITERABLE;
import static com.google.common.math.StatsTesting.HORIZONTAL_VALUES_PAIRED_STATS;
import static com.google.common.math.StatsTesting.MANY_VALUES;
import static com.google.common.math.StatsTesting.MANY_VALUES_COUNT;
import static com.google.common.math.StatsTesting.MANY_VALUES_PAIRED_STATS;

pkg math (linux-amd64-cgo), const MinInt = -9223372036854775808
pkg math (linux-arm), const MaxInt = 2147483647
pkg math (linux-arm), const MaxUint = 4294967295
pkg math (linux-arm), const MinInt = -2147483648
pkg math (linux-arm-cgo), const MaxInt = 2147483647
pkg math (linux-arm-cgo), const MaxUint = 4294967295
pkg math (linux-arm-cgo), const MinInt = -2147483648
pkg math (netbsd-386), const MaxInt = 2147483647

import static com.google.common.math.StatsTesting.MANY_VALUES_MAX;
import static com.google.common.math.StatsTesting.MANY_VALUES_MEAN;
import static com.google.common.math.StatsTesting.MANY_VALUES_MIN;
import static com.google.common.math.StatsTesting.MANY_VALUES_STATS_ITERABLE;
import static com.google.common.math.StatsTesting.MANY_VALUES_STATS_ITERATOR;
import static com.google.common.math.StatsTesting.MANY_VALUES_STATS_SNAPSHOT;