Caffe2 - Python API
A deep learning, cross platform ML framework
Public Member Functions | Public Attributes | List of all members
caffe2.python.layer_test_util.LayersTestCase Class Reference
Inheritance diagram for caffe2.python.layer_test_util.LayersTestCase:

Public Member Functions

def setUp (self)
def setup_example (self)
def reset_model (self, input_feature_schema=None, trainer_extra_schema=None)
def new_record (self, schema_obj)
def get_training_nets (self, add_constants=False)
def get_eval_net (self)
def get_predict_net (self)
def run_train_net (self)
def run_train_net_forward_only (self, num_iter=1)
def assertBlobsEqual (self, spec_blobs, op_blobs)
def assertArgsEqual (self, spec_args, op_args)
def assertNetContainOps (self, net, op_specs)
- Public Member Functions inherited from caffe2.python.test_util.TestCase
def setUpClass (cls)
def setUp (self)
def tearDown (self)

Public Attributes

- Public Attributes inherited from caffe2.python.test_util.TestCase

Detailed Description

Definition at line 30 of file

Member Function Documentation

def caffe2.python.layer_test_util.LayersTestCase.assertBlobsEqual (   self,
spec_blobs can either be None or a list of blob names. If it's None,
then no assertion is performed. The elements of the list can be None,
in that case, it means that position will not be checked.

Definition at line 96 of file

def caffe2.python.layer_test_util.LayersTestCase.assertNetContainOps (   self,
Given a net and a list of OpSpec's, check that the net match the spec

Definition at line 125 of file

def caffe2.python.layer_test_util.LayersTestCase.get_training_nets (   self,
  add_constants = False 
We don't use
here because it includes initialization of global constants, which make
testing tricky

Definition at line 57 of file

def caffe2.python.layer_test_util.LayersTestCase.setup_example (   self)
This is undocumented feature in hypothesis,

Definition at line 36 of file

The documentation for this class was generated from the following file: