spaceToBatchND doc fixes (tensorflow#1411)

DOC

src/ops/array_ops.ts

@@ -817,17 +817,17 @@ function batchToSpaceND_<T extends Tensor>(
 }
 
 /**
- * This operation divides "spatial" dimensions [1, ..., M] of the input into
- * a grid of blocks of shape block_shape, and interleaves these blocks with
+ * This operation divides "spatial" dimensions `[1, ..., M]` of the input into
+ * a grid of blocks of shape `blockShape`, and interleaves these blocks with
  * the "batch" dimension (0) such that in the output, the spatial
- * dimensions [1, ..., M] correspond to the position within the grid,
+ * dimensions `[1, ..., M]` correspond to the position within the grid,
  * and the batch dimension combines both the position within a spatial block
  * and the original batch position. Prior to division into blocks,
  * the spatial dimensions of the input are optionally zero padded
- * according to paddings. See below for a precise description.
+ * according to `paddings`. See below for a precise description.
  *
  * ```js
- * const x = tf.tensor4d([1, 2, 3, 4], [4, 1, 1, 1]);
+ * const x = tf.tensor4d([1, 2, 3, 4], [1, 2, 2, 1]);
  * const blockShape = [2, 2];
  * const paddings = [[0, 0], [0, 0]];
  *
@@ -836,33 +836,31 @@ function batchToSpaceND_<T extends Tensor>(
  *
  * @param x A `tf.Tensor`. N-D with `x.shape` = `[batch] + spatialShape +
  * remainingShape`, where spatialShape has `M` dimensions.
- * @param blockShape A 1-D array. Must be one of the following types: `int32`,
- * `int64`. Must have shape `[M]`, all values must be >= 1.
- * @param paddings A 2-D array.  Must be one of the following types: `int32`,
- * `int64`. Must have shape `[M, 2]`, all values must be >= 0. `paddings[i] =
- * [padStart, padEnd]` specifies the amount to zero-pad from input dimension
- * `i + 1`, which corresponds to spatial dimension `i`.
- * It is required that
+ * @param blockShape A 1-D array. Must have shape `[M]`, all values must
+ * be >= 1.
+ * @param paddings A 2-D array. Must have shape `[M, 2]`, all values must be >=
+ *     0. `paddings[i] = [padStart, padEnd]` specifies the amount to zero-pad
+ * from input dimension `i + 1`, which corresponds to spatial dimension `i`. It
+ * is required that
  * `(inputShape[i + 1] + padStart + padEnd) % blockShape[i] === 0`
  *
  * This operation is equivalent to the following steps:
  *
- * 1. Zero-pad the start and end of dimensions [1, ..., M] of the input
- * according to paddings to produce padded of shape padded_shape.
+ * 1. Zero-pad the start and end of dimensions `[1, ..., M]` of the input
+ * according to `paddings` to produce `padded` of shape paddedShape.
  *
- * 2. Reshape padded to reshaped_padded of shape:
- * [batch] + [padded_shape[1] / block_shape[0], block_shape[0], ...,
- * padded_shape[M] / block_shape[M-1], block_shape[M-1]] + remaining_shape
+ * 2. Reshape `padded` to `reshapedPadded` of shape:
+ * `[batch] + [paddedShape[1] / blockShape[0], blockShape[0], ...,
+ * paddedShape[M] / blockShape[M-1], blockShape[M-1]] + remainingShape`
  *
- * 3. Permute dimensions of reshaped_padded to produce permuted_
- * reshaped_padded of shape:
- * block_shape + [batch] + [padded_shape[1] / block_shape[0], ...,
- * padded_shape[M] / block_shape[M-1]] + remaining_shape
+ * 3. Permute dimensions of `reshapedPadded` to produce `permutedReshapedPadded`
+ * of shape: `blockShape + [batch] + [paddedShape[1] / blockShape[0], ...,
+ * paddedShape[M] / blockShape[M-1]] + remainingShape`
  *
- * 4. Reshape permuted_reshaped_padded to flatten block_shape into the
+ * 4. Reshape `permutedReshapedPadded` to flatten `blockShape` into the
  * batch dimension, producing an output tensor of shape:
- * [batch * prod(block_shape)] + [padded_shape[1] / block_shape[0], ...,
- * padded_shape[M] / block_shape[M-1]] + remaining_shape
+ * `[batch * prod(blockShape)] + [paddedShape[1] / blockShape[0], ...,
+ * paddedShape[M] / blockShape[M-1]] + remainingShape`
  */
 /** @doc {heading: 'Tensors', subheading: 'Transformations'} */
 function spaceToBatchND_<T extends Tensor>(