Function _format_tensor

src/transformers/testing_utils.py:3889–3956

Format torch's tensor in a pretty way to be shown 👀 in the test report.

(t, indent_level=0, sci_mode=None)

def _format_tensor(t, indent_level=0, sci_mode=None):
    class="st">""class="st">"Format torch&class="cm">#x27;s tensor in a pretty way to be shown 👀 in the test report."class="st">""

    class="cm"># `torch.testing.assert_close` could accept python int/float numbers.
    if not isinstance(t, torch.Tensor):
        t = torch.tensor(t)

    class="cm"># Simply make the processing below simpler (not to handle both cases)
    is_scalar = False
    if t.ndim == 0:
        t = torch.tensor([t])
        is_scalar = True

    class="cm"># For scalar or one-dimensional tensor, keep it as one-line. If there is only one element along any dimension except
    class="cm"># the last one, we also keep it as one-line.
    if t.ndim <= 1 or set(t.shape[0:-1]) == {1}:
        class="cm"># Use `detach` to remove `grad_fn=<...>`, and use `to(class="st">"cpu")` to remove `device=class="st">'...'`
        t = t.detach().to(class="st">"cpu")

        class="cm"># We work directly with the string representation instead the tensor itself
        t_str = str(t)

        class="cm"># remove `tensor( ... )` so keep only the content
        t_str = t_str.replace(class="st">"tensor(", class="st">"").replace(class="st">")", class="st">"")

        class="cm"># Sometimes there are extra spaces between `[` and the first digit of the first value (for alignment).
        class="cm"># For example `[[ 0.06, -0.51], [-0.76, -0.49]]`. It may have multiple consecutive spaces.
        class="cm"># Let's remove such extra spaces.
        while class="st">"[ " in t_str:
            t_str = t_str.replace(class="st">"[ ", class="st">"[")

        class="cm"># Put everything in a single line. We replace `\n` by a space ` ` so we still keep `,\n` as `, `.
        t_str = t_str.replace(class="st">"\n", class="st">" ")

        class="cm"># Remove repeated spaces (introduced by the previous step)
        while class="st">"  " in t_str:
            t_str = t_str.replace(class="st">"  ", class="st">" ")

        class="cm"># remove leading `[` and `]` for scalar tensor
        if is_scalar:
            t_str = t_str[1:-1]

        t_str = class="st">" " * 4 * indent_level + t_str

        return t_str

    class="cm"># Otherwise, we separate the representations of each element along an outer dimension by new lines (after a `,`).
    class="cm"># The representation of each element is obtained by calling this function recursively with current `indent_level`.
    else:
        t_str = str(t)

        class="cm"># (For the recursive calls should receive this value)
        if sci_mode is None:
            sci_mode = class="st">"e+" in t_str or class="st">"e-" in t_str

        class="cm"># Use the original content to determine the scientific mode to use. This is required as the representation of
        class="cm"># t[index] (computed below) maybe have different format regarding scientific notation.
        torch.set_printoptions(sci_mode=sci_mode)