Easy Framework

Tensor Indexing and Slicing

Select whole rows from a matrix, in the order requested. Each selected row keeps all its columns.

Your task

Implement select_rows(x, rows).

x is a two-dimensional tensor of shape (m, n).
rows is a Python list of valid, zero-based integer row positions in [0, m).
Return shape (len(rows), n), with x's dtype and device. Leave x unchanged.

For x=[[10, 11], [20, 21], [30, 31]] and rows=[2, 0, 2], return [[30, 31], [10, 11], [30, 31]]. Row 2 appears twice because it was requested twice. Do not sort or deduplicate the indices.

Selecting one row still produces a matrix of shape (1, n). An empty list produces shape (0, n): the result has no rows but keeps its column dimension. This task uses a list of row positions, rather than a contiguous slice or a boolean mask.

In PyTorch, use x[rows]. In JAX, convert the list explicitly to integer indices: x[jnp.array(rows, dtype=jnp.int32)]. The explicit dtype also handles an empty list, which would otherwise become a floating-point array.

Understand the ideas behind this exercise. The Problem tab contains the exact implementation requirements.

Select values using coordinates

A slice selects a regularly spaced region of an array. A gather selects entries using supplied indices. Check whether those indices select whole rows or columns, or a different entry within each row.

For [[10, 11], [20, 21]], choosing column 1 from the first row and column 0 from the second gives [11, 20]. Choosing columns [1, 0] from every row instead gives [[11, 10], [21, 20]]. These operations use the same index values but have different meanings and output shapes.

Scatter writes values to selected destinations

Scatter takes values and destination indices. The operation may replace existing values or combine them using a reduction such as addition.

Starting with [0, 0, 0], scatter-add of values [2, 3] at indices [1, 1] gives [0, 5, 0]. Both values contribute to the repeated destination. Repeated assignment is not equivalent to this sum; follow the operation's rule for repeated indices.

Selecting with a mask differs from replacing with a mask

For values [10, 20, 30] and mask [True, False, True], selecting masked entries gives [10, 30]. Replacing masked entries with zero gives [0, 20, 0]. Selection can change the shape; replacement preserves it. A selection whose size depends on runtime values needs particular care in compiled code with fixed output shapes.

Check whether an update changes the original array

JAX indexed updates return a new array value. In PyTorch, basic slicing can return a view that shares storage, while advanced indexing returns a copy. Modifying a selected copy does not modify the source. Direct indexed assignment is a separate operation, so distinguish changing a selection from assigning into the original.

Detecting runtime…

Tensor Indexing and Slicing

Your task

Select values using coordinates

Scatter writes values to selected destinations

Selecting with a mask differs from replacing with a mask

Check whether an update changes the original array

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