title: TensorFlow, Large-scale machine learning on heterogeneous systems

   * the internal list.
   */
  @JvmStatic
  fun fragmentBuffer(buffer: Buffer): Buffer {
    // Write each byte into a new buffer, then clone it so that the segments are shared.
    // Shared segments cannot be compacted so we'll get a long chain of short segments.
    val result = Buffer()
    while (!buffer.exhausted()) {
      val box = Buffer()
      box.write(buffer, 1)

then the <code>File</code> interface is implemented by both <code>S1</code> and
<code>S2</code>, regardless of what other methods
<code>S1</code> and <code>S2</code> may have or share.
</p>

<p>
Every type that is a member of the type set of an interface implements that interface.
Any given type may implement several distinct interfaces.

        )
        assert response.status_code == 200, response.text
        response = client.post(
            "/heroes/", json={"name": "Rusty-Man", "secret_name": "Tommy Sharp"}
        )
        assert response.status_code == 200, response.text

        response = client.get("/heroes/")
        assert response.status_code == 200, response.text
        assert response.json() == snapshot(

    new_field.post_validators = field.post_validators  # type: ignore[attr-defined]
    new_field.parse_json = field.parse_json  # type: ignore[attr-defined]
    new_field.shape = field.shape  # type: ignore[attr-defined]
    new_field.populate_validators()  # type: ignore[attr-defined]
    return new_field


def generate_operation_id_for_path(
    *, name: str, path: str, method: str

 * the License.
 */

package com.google.common.base;

import com.google.common.annotations.GwtCompatible;

/**
 * The subset of the {@link java.util.regex.Pattern} API which is used by this package, and also
 * shared with the {@code re2j} library. For internal use only. Please refer to the {@code Pattern}
 * javadoc for details.
 */
@GwtCompatible
@ElementTypesAreNonnullByDefault
abstract class CommonPattern {

TFE_Op* MatMulOp(TFE_Context* ctx, TFE_TensorHandle* a, TFE_TensorHandle* b);

// Return an identity op.
TFE_Op* IdentityOp(TFE_Context* ctx, TFE_TensorHandle* a);

// Return a shape op fetching the shape of `a`.
TFE_Op* ShapeOp(TFE_Context* ctx, TFE_TensorHandle* a);

// Return an allreduce op adding up input tensor `in` from `group_size` workers.

 * the License.
 */

package com.google.common.base;

import com.google.common.annotations.GwtCompatible;

/**
 * The subset of the {@link java.util.regex.Pattern} API which is used by this package, and also
 * shared with the {@code re2j} library. For internal use only. Please refer to the {@code Pattern}
 * javadoc for details.
 */
@GwtCompatible
@ElementTypesAreNonnullByDefault
abstract class CommonPattern {

}

TEST(CAPI, ShapeInferenceError) {
  // TF_FinishOperation should fail if the shape of the added operation cannot
  // be inferred.
  TF_Status* status = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Create this failure by trying to add two nodes with incompatible shapes
  // (A tensor with shape [2] and a tensor with shape [3] cannot be added).
  const char data[] = {1, 2, 3};
  const int64_t vec2_dims[] = {2};

/build-logic-settings/                      @gradle/bt-developer-productivity
/build.gradle*                              @gradle/bt-developer-productivity
/settings.gradle*                           @gradle/bt-developer-productivity
gradle/shared-with-buildSrc/                @gradle/bt-developer-productivity
platforms/build-infrastructure/             @gradle/bt-developer-productivity
subprojects/internal-build-reports/         @gradle/bt-developer-productivity