export function parseDebugTensorValue()

in tensorboard/plugins/debugger_v2/tf_debugger_v2_plugin/store/debug_tensor_value.ts [99:213]

• 107 lines of code
• 24 McCabe index (conditional complexity)

export function parseDebugTensorValue(
  raw: RawDebugTensorValue
): DebugTensorValue {
  const {tensorDebugMode, array} = raw;
  switch (tensorDebugMode) {
    case TensorDebugMode.NO_TENSOR: {
      if (array !== null) {
        throw new Error(
          'Unexpectedly received non-null debug-tensor-value array ' +
            'under NO_TENSOR mode'
        );
      }
      return {};
    }
    case TensorDebugMode.CURT_HEALTH: {
      if (array === null || array.length !== 2) {
        throw new Error(
          `Under CURT_HEALTH mode, expected debug-tensor-value array ` +
            `to have length 2, but got ${JSON.stringify(array)}`
        );
      }
      return {
        hasInfOrNaN: Boolean(array[1]),
      };
    }
    case TensorDebugMode.CONCISE_HEALTH: {
      if (array === null || array.length !== 5) {
        throw new Error(
          `Under CONCISE_HEALTH mode, expected debug-tensor-value array ` +
            `to have length 5, but got ${JSON.stringify(array)}`
        );
      }
      const value: DebugTensorValue = {
        size: array[1],
      };
      if (array[2] > 0) {
        value.numNegativeInfs = array[2];
      }
      if (array[3] > 0) {
        value.numPositiveInfs = array[3];
      }
      if (array[4] > 0) {
        value.numNaNs = array[4];
      }
      return value;
    }
    case TensorDebugMode.SHAPE: {
      if (array === null || array.length !== 10) {
        throw new Error(
          `Under SHAPE mode, expected debug-tensor-value array ` +
            `to have length 10, but got ${JSON.stringify(array)}`
        );
      }
      const rank = array[2];
      let shape: number[] = array.slice(4, Math.min(4 + rank, array.length));
      if (shape.length < rank) {
        // The SHAPE mode truncates the shape at head.
        shape = new Array<number>(rank - shape.length).concat(shape);
      }
      return {
        dtype: DTYPE_ENUM_TO_NAME[array[1]],
        rank,
        size: array[3],
        shape,
      };
    }
    case TensorDebugMode.FULL_HEALTH: {
      if (array === null || array.length !== 11) {
        throw new Error(
          `Under FULL_HEALTH mode, expected debug-tensor-value array ` +
            `to have length 11, but got ${JSON.stringify(array)}`
        );
      }
      const rank = array[3];
      const value: DebugTensorValue = {
        dtype: DTYPE_ENUM_TO_NAME[array[2]],
        rank,
        size: array[4],
      };
      if (array[5] > 0) {
        value.numNegativeInfs = array[5];
      }
      if (array[6] > 0) {
        value.numPositiveInfs = array[6];
      }
      if (array[7] > 0) {
        value.numNaNs = array[7];
      }
      if (array[8] > 0) {
        value.numNegativeFinites = array[8];
      }
      if (array[9] > 0) {
        value.numZeros = array[9];
      }
      if (array[10] > 0) {
        value.numPositiveFinites = array[10];
      }
      return value;
    }
    case TensorDebugMode.FULL_TENSOR: {
      // Under FULL_TENSOR mode, the full tensor value is supplied via
      // separate means. No summary values are provided for the tensor value.
      if (array !== null) {
        throw new Error(
          'Unexpectedly received non-null debug-tensor-value array ' +
            'under FULL_TENSOR mode'
        );
      }
      return {};
    }
    default: {
      throw new Error(`Unrecognized tensorDebugMode: ${tensorDebugMode}`);
    }
  }
}