if v != byte(l+i) {
						t.Fatalf("in %d,%d: Next(%d)[%d] = %d, want %d", i, j, k, l, v, l+i)
					}
				}
			}
		}
	}
}

var readBytesTests = []struct {
	buffer   string
	delim    byte
	expected []string
	err      error
}{
	{"", 0, []string{""}, io.EOF},
	{"a\x00", 0, []string{"a\x00"}, nil},
	{"abbbaaaba", 'b', []string{"ab", "b", "b", "aaab"}, nil},

  ASSERT_EQ(num_dims, -1);
  ASSERT_EQ("Invalid handle", string(TF_Message(status.get())));

  TF_SetStatus(status.get(), TF_OK, "");

  int dim = TFE_TensorHandleDim(h, 0, status.get());
  ASSERT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(status.get()));
  ASSERT_EQ(dim, -1);
  ASSERT_EQ("Invalid handle", string(TF_Message(status.get())));
}

TEST(CAPI, TensorHandleDevices) {

  auto dtype = TFE_TensorHandleDataType(t->tensor);
  TFE_CustomDeviceTensorHandleMethods handle_methods;
  handle_methods.num_dims = &LoggedTensorNumDims;
  handle_methods.dim = &LoggedTensorDim;
  handle_methods.deallocator = &LoggedTensorDeallocator;
  return TFE_NewCustomDeviceTensorHandle(context, logging_device_name.c_str(),
                                         dtype, t.release(), handle_methods,

ction(c){var d=!1;e.valAttr("dimension")&&(d=a.formUtils.checkImageDimension(c,e.valAttr("dimension"),h)),!d&&e.valAttr("ratio")&&(d=a.formUtils.checkImageRatio(c,e.valAttr("ratio"),h)),d?(j.errorMessage=h.wrongFileDim+" "+e.valAttr("has-not-valid-dim"),b(!1)):b(!0)},function(a){throw a})}else b(!0)},errorMessage:"",errorMessageKey:""}),a(b).one("validatorsLoaded formValidationSetup",function(b,c,d){var e;e=c?c.find('input[type="file"]'):a('input[type="file"]'),a.formUtils.dialogs.removeInputSty...

		for i := 0; i < n; i++ {
			buf.WriteString("abcdefg")
		}

		r := NewReaderSize(&buf, minReadBufferSize)
		readTo := func(delim byte, want string) {
			data, err := read(r, delim)
			if err != nil {
				t.Fatalf("#%d: unexpected error reading to %c: %v", rno, delim, err)
			}
			if got := string(data); got != want {
				t.Fatalf("#%d: got %q, want %q", rno, got, want)
			}
		}

    void tryClose() {
        synchronized (LOCK) {

            /* Yes, there is the potential to drop packets
             * because we might close the socket during a
             * request. However the chances are slim and the
             * retry code should ensure the overall request
             * is serviced. The alternative complicates things
             * more than I think is worth it.
             */

// Information about the shape of a Tensor and its type.
struct TF_ShapeAndType {
  // Number of dimensions. -1 indicates unknown rank.
  int num_dims;
  // Array of dimensions. -1 indicates unknown dim.
  int64_t* dims;
  // The data type. May be 0 to denote unknown type.
  TF_DataType dtype;
};

typedef struct TF_ShapeAndType TF_ShapeAndType;

// A list of TF_ShapeAndType elements..

      shape.dims = nullptr;
      continue;
    }
    shape.dims = new int64_t[shape.num_dims];
    for (size_t j = 0; j < shape.num_dims; ++j) {
      shape.dims[j] = c.Value(c.Dim(shape_handle, j));
    }
  }
  if (output_shapes != nullptr) *output_shapes = output_shapes_result;

  // TODO(bgogul): Set output_resource_shapes_and_types.
}

        synchronized (this.LOCK) {

            /*
             * Yes, there is the potential to drop packets
             * because we might close the socket during a
             * request. However the chances are slim and the
             * retry code should ensure the overall request
             * is serviced. The alternative complicates things
             * more than I think is worth it.
             */

    return;
  }

  // Rank is greater than 0, so fill in the values, if known, and
  // -1 for unknown values.
  for (int i = 0; i < num_dims; ++i) {
    auto dim = ic->Dim(shape, i);
    int64_t value = -1;
    if (ic->ValueKnown(dim)) {
      value = ic->Value(dim);
    }
    dims[i] = value;
  }
}

// TF_OperationDescription functions ------------------------------------------

extern "C" {