Creates an empty UnitTest.

Prints a (const) char array of 'len' elements, starting at address 'begin'.

Restores the test order to before the first shuffle.

Checks if str contains '=', '&', '%' or '\n' characters. If yes, replaces them by "%xx" where xx is their hexadecimal value. For example, replaces "="

Creates an ANSI string from the given wide string, allocating memory using new. The caller is responsible for deleting the return value using delete[]

Adds a failure if the key is a reserved attribute of Google Test testcase tags. Returns true if the property is valid.

Verifies that registered_tests match the test names in defined_test_names_; returns registered_tests if successful, or aborts the program otherwise.

Waits for the child in a death test to exit, returning its exit status, or 0 if no child process exists. As a side effect, sets the outcome data memb

Will not return until the internal thread has exited. */

Compares two wide C strings. Returns true iff they have the same content. Unlike wcscmp(), this function can handle NULL argument(s). A NULL C stri

Creates a new XmlUnitTestResultPrinter.

Backward pass: prepare diffs and run the net backward. Take diffs: list of diffs to return in addition to bottom diffs. kwargs: Keys

Batch blob lists according to net's batch size. Take blobs: Keys blob names and values are lists of blobs (of any length). Na

An OrderedDict (bottom to top, i.e., input to output) of network blobs indexed by name

Invert Caffe formatting; see Net.preprocess().

Forward pass: prepare inputs and run the net forward. Take blobs: list of blobs to return in addition to output blobs. kwargs: Keys

Run net forward in batches. Take blobs: list of blobs to extract as in forward() kwargs: Keys are input blob names and values are bl

Run net forward + backward in batches. Take blobs: list of blobs to extract as in forward() diffs: list of diffs to extract as in ba

An OrderedDict (bottom to top, i.e., input to output) of network parameters indexed by name; each is a list of multiple blobs (e.g., weig

Format input for Caffe: - convert to single - resize to input dimensions (preserving number of channels) - reorder channels (for inst

Set the input channel order for e.g. RGB to BGR conversion as needed for the reference ImageNet model. Take input_: which input to a

Set input arrays of the in-memory MemoryDataLayer. (Note: this is only for networks declared with the memory data layer.)

Set the scale of preprocessed inputs s.t. the blob = blob * scale. N.B. input_scale is done AFTER mean subtraction and other preprocessing

Set the mean to subtract for data centering. Take input_: which input to assign this mean. mean: mean K x H x W ndarray (input dimen

Set the scale of raw features s.t. the input blob = input * scale. While Python represents images in [0, 1], certain Caffe models like Ca

Take image_dims: dimensions to scale input for cropping/sampling. Default is to scale to net input size for whole-image c

Take gpu, mean, input_scale, raw_scale, channel_swap: params for preprocessing options. context_pad: amount of su