FM / python

/usr/local/lib64/python3.6/site-packages/caffe2/python/

/usr/local/lib64/python3.6/site-packages/caffe2/python

Name	Size	Mode	Actions
docs/	-	0755	rm
examples/	-	0755	rm
fakelowp/	-	0755	rm
helpers/	-	0755	rm
ideep/	-	0755	rm
layers/	-	0755	rm
mint/	-	0755	rm
mkl/	-	0755	rm
modeling/	-	0755	rm
models/	-	0755	rm
onnx/	-	0755	rm
operator_test/	-	0755	rm
predictor/	-	0755	rm
rnn/	-	0755	rm
serialized_test/	-	0755	rm
test/	-	0755	rm
trt/	-	0755	rm
__pycache__/	-	0755	rm
allcompare_test.py	2255	0644	edit dl rm
attention.py	12359	0644	edit dl rm
benchmark_generator.py	4912	0644	edit dl rm
binarysize.py	5521	0644	edit dl rm
brew.py	4762	0644	edit dl rm
brew_test.py	11739	0644	edit dl rm
build.py	153	0644	edit dl rm
cached_reader.py	4394	0644	edit dl rm
caffe2_pybind11_state.cpython-36m-x86_64-linux-gnu.so	48299712	0755	edit dl rm
caffe2_pybind11_state_gpu.cpython-36m-x86_64-linux-gnu.so	49048144	0755	edit dl rm
caffe_translator.py	35227	0644	edit dl rm
caffe_translator_test.py	3553	0644	edit dl rm
checkpoint.py	32101	0644	edit dl rm
checkpoint_test.py	13405	0644	edit dl rm
cnn.py	7626	0644	edit dl rm
context.py	2841	0644	edit dl rm
context_test.py	1792	0644	edit dl rm
control.py	19309	0644	edit dl rm
control_ops_grad.py	28893	0644	edit dl rm
control_ops_grad_test.py	1752	0644	edit dl rm
control_ops_util.py	10863	0644	edit dl rm
control_test.py	12276	0644	edit dl rm
convert.py	55	0644	edit dl rm
convert_test.py	201	0644	edit dl rm
convnet_benchmarks.py	20533	0644	edit dl rm
convnet_benchmarks_test.py	839	0644	edit dl rm
core.py	119400	0644	edit dl rm
core_gradients_test.py	38022	0644	edit dl rm
core_test.py	47683	0644	edit dl rm
crf.py	13250	0644	edit dl rm
crf_predict.py	1159	0644	edit dl rm
crf_viterbi_test.py	1663	0644	edit dl rm
dataio.py	23532	0644	edit dl rm
dataio_test.py	17575	0644	edit dl rm
dataset.py	12886	0644	edit dl rm
data_parallel_model.py	83100	0644	edit dl rm
data_parallel_model_test.py	56145	0644	edit dl rm
data_workers.py	15941	0644	edit dl rm
data_workers_test.py	6561	0644	edit dl rm
db_file_reader.py	6608	0644	edit dl rm
db_test.py	1110	0644	edit dl rm
device_checker.py	5157	0644	edit dl rm
dyndep.py	1533	0644	edit dl rm
embedding_generation_benchmark.py	5256	0644	edit dl rm
experiment_util.py	3625	0644	edit dl rm
extension_loader.py	744	0644	edit dl rm
fakefp16_transform_lib.py	322	0644	edit dl rm
filler_test.py	748	0644	edit dl rm
functional.py	4415	0644	edit dl rm
functional_test.py	4204	0644	edit dl rm
fused_8bit_rowwise_conversion_ops_test.py	3945	0644	edit dl rm
gradient_checker.py	15377	0644	edit dl rm
gradient_check_test.py	20729	0644	edit dl rm
gru_cell.py	5129	0644	edit dl rm
hip_test_util.py	405	0644	edit dl rm
hsm_util.py	2259	0644	edit dl rm
hypothesis_test.py	105762	0644	edit dl rm
hypothesis_test_util.py	26853	0644	edit dl rm
ideep_test_util.py	998	0644	edit dl rm
layers_test.py	92931	0644	edit dl rm
layer_model_helper.py	29340	0644	edit dl rm
layer_model_instantiator.py	3935	0644	edit dl rm
layer_parameter_sharing_test.py	9148	0644	edit dl rm
layer_test_util.py	4875	0644	edit dl rm
lazy.py	277	0644	edit dl rm
lazy_dyndep.py	2562	0644	edit dl rm
lazy_dyndep_test.py	3914	0644	edit dl rm
lengths_reducer_fused_8bit_rowwise_ops_test.py	7575	0644	edit dl rm
lengths_reducer_rowwise_8bit_ops_test.py	5710	0644	edit dl rm
lstm_benchmark.py	10649	0644	edit dl rm
memonger.py	34041	0644	edit dl rm
memonger_test.py	36910	0644	edit dl rm
mkl_test_util.py	1142	0644	edit dl rm
model_device_test.py	4777	0644	edit dl rm
model_helper.py	23492	0644	edit dl rm
model_helper_test.py	2336	0644	edit dl rm
modifier_context.py	1772	0644	edit dl rm
muji.py	8131	0644	edit dl rm
muji_test.py	3058	0644	edit dl rm
net_builder.py	27679	0644	edit dl rm
net_builder_test.py	11382	0644	edit dl rm
net_drawer.py	14264	0644	edit dl rm
net_printer.py	12704	0644	edit dl rm
net_printer_test.py	3190	0644	edit dl rm
nomnigraph.py	4216	0644	edit dl rm
nomnigraph_test.py	15427	0644	edit dl rm
nomnigraph_transformations.py	3787	0644	edit dl rm
nomnigraph_transformations_test.py	5767	0644	edit dl rm
normalizer.py	1411	0644	edit dl rm
normalizer_context.py	1007	0644	edit dl rm
normalizer_test.py	487	0644	edit dl rm
numa_benchmark.py	2230	0644	edit dl rm
numa_test.py	1663	0644	edit dl rm
observer_test.py	5316	0644	edit dl rm
operator_fp_exceptions_test.py	1248	0644	edit dl rm
optimizer.py	78813	0644	edit dl rm
optimizer_context.py	1462	0644	edit dl rm
optimizer_test.py	30705	0644	edit dl rm
optimizer_test_util.py	9187	0644	edit dl rm
parallelize_bmuf_distributed_test.py	9908	0644	edit dl rm
parallel_workers.py	7682	0644	edit dl rm
parallel_workers_test.py	3501	0644	edit dl rm
pipeline.py	17283	0644	edit dl rm
pipeline_test.py	2542	0644	edit dl rm
predictor_constants.py	198	0644	edit dl rm
python_op_test.py	9169	0644	edit dl rm
queue_util.py	4459	0644	edit dl rm
record_queue.py	4453	0644	edit dl rm
recurrent.py	13297	0644	edit dl rm
regularizer.py	21120	0644	edit dl rm
regularizer_context.py	1013	0644	edit dl rm
regularizer_test.py	10266	0644	edit dl rm
rnn_cell.py	68233	0644	edit dl rm
schema.py	45621	0644	edit dl rm
schema_test.py	15754	0644	edit dl rm
scope.py	3623	0644	edit dl rm
scope_test.py	5249	0644	edit dl rm
session.py	7642	0644	edit dl rm
session_test.py	2078	0644	edit dl rm
sparse_to_dense_mask_test.py	6565	0644	edit dl rm
sparse_to_dense_test.py	3556	0644	edit dl rm
task.py	24274	0644	edit dl rm
task_test.py	870	0644	edit dl rm
test_util.py	3524	0644	edit dl rm
text_file_reader.py	1990	0644	edit dl rm
timeout_guard.py	4054	0644	edit dl rm
toy_regression_test.py	2822	0644	edit dl rm
transformations.py	1832	0644	edit dl rm
transformations_test.py	11960	0644	edit dl rm
tt_core.py	9349	0644	edit dl rm
tt_core_test.py	2518	0644	edit dl rm
utils.py	14181	0644	edit dl rm
utils_test.py	1399	0644	edit dl rm
visualize.py	6315	0644	edit dl rm
workspace.py	25263	0644	edit dl rm
workspace_test.py	34844	0644	edit dl rm
_import_c_extension.py	2250	0644	edit dl rm
__init__.py	3925	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/caffe2/python/observer_test.py (5316B)

import numpy as np
import unittest
from hypothesis import given, settings
import hypothesis.strategies as st

from caffe2.python import brew, core, model_helper, rnn_cell
import caffe2.python.workspace as ws

class TestObservers(unittest.TestCase):
    def setUp(self):
        core.GlobalInit(["python", "caffe2"])
        ws.ResetWorkspace()
        self.model = model_helper.ModelHelper()
        brew.fc(self.model, "data", "y",
                    dim_in=4, dim_out=2,
                    weight_init=('ConstantFill', dict(value=1.0)),
                    bias_init=('ConstantFill', dict(value=0.0)),
                    axis=0)
        ws.FeedBlob("data", np.zeros([4], dtype='float32'))

ws.RunNetOnce(self.model.param_init_net)
        ws.CreateNet(self.model.net)

def testObserver(self):
        ob = self.model.net.AddObserver("TimeObserver")
        ws.RunNet(self.model.net)
        print(ob.average_time())
        num = self.model.net.NumObservers()
        self.model.net.RemoveObserver(ob)
        assert(self.model.net.NumObservers() + 1 == num)

@given(
        num_layers=st.integers(1, 4),
        forward_only=st.booleans()
    )
    @settings(deadline=1000)
    def test_observer_rnn_executor(self, num_layers, forward_only):
        '''
        Test that the RNN executor produces same results as
        the non-executor (i.e running step nets as sequence of simple nets).
        '''

Tseq = [2, 3, 4]
        batch_size = 10
        input_dim = 3
        hidden_dim = 3

run_cnt = [0] * len(Tseq)
        avg_time = [0] * len(Tseq)
        for j in range(len(Tseq)):
            T = Tseq[j]

ws.ResetWorkspace()
            ws.FeedBlob(
                "seq_lengths",
                np.array([T] * batch_size, dtype=np.int32)
            )
            ws.FeedBlob("target", np.random.rand(
                T, batch_size, hidden_dim).astype(np.float32))
            ws.FeedBlob("hidden_init", np.zeros(
                [1, batch_size, hidden_dim], dtype=np.float32
            ))
            ws.FeedBlob("cell_init", np.zeros(
                [1, batch_size, hidden_dim], dtype=np.float32
            ))

model = model_helper.ModelHelper(name="lstm")
            model.net.AddExternalInputs(["input"])

init_blobs = []
            for i in range(num_layers):
                hidden_init, cell_init = model.net.AddExternalInputs(
                    "hidden_init_{}".format(i),
                    "cell_init_{}".format(i)
                )
                init_blobs.extend([hidden_init, cell_init])

output, last_hidden, _, last_state = rnn_cell.LSTM(
                model=model,
                input_blob="input",
                seq_lengths="seq_lengths",
                initial_states=init_blobs,
                dim_in=input_dim,
                dim_out=[hidden_dim] * num_layers,
                drop_states=True,
                forward_only=forward_only,
                return_last_layer_only=True,
            )

loss = model.AveragedLoss(
                model.SquaredL2Distance([output, "target"], "dist"),
                "loss"
            )
            # Add gradient ops
            if not forward_only:
                model.AddGradientOperators([loss])

# init
            for init_blob in init_blobs:
                ws.FeedBlob(init_blob, np.zeros(
                    [1, batch_size, hidden_dim], dtype=np.float32
                ))
            ws.RunNetOnce(model.param_init_net)

# Run with executor
            self.enable_rnn_executor(model.net, 1, forward_only)

np.random.seed(10022015)
            input_shape = [T, batch_size, input_dim]
            ws.FeedBlob(
                "input",
                np.random.rand(*input_shape).astype(np.float32)
            )
            ws.FeedBlob(
                "target",
                np.random.rand(
                    T,
                    batch_size,
                    hidden_dim
                ).astype(np.float32)
            )
            ws.CreateNet(model.net, overwrite=True)

time_ob = model.net.AddObserver("TimeObserver")
            run_cnt_ob = model.net.AddObserver("RunCountObserver")
            ws.RunNet(model.net)
            avg_time[j] = time_ob.average_time()
            run_cnt[j] = int(''.join(x for x in run_cnt_ob.debug_info() if x.isdigit()))
            model.net.RemoveObserver(time_ob)
            model.net.RemoveObserver(run_cnt_ob)

print(avg_time)
        print(run_cnt)
        self.assertTrue(run_cnt[1] > run_cnt[0] and run_cnt[2] > run_cnt[1])
        self.assertEqual(run_cnt[1] - run_cnt[0], run_cnt[2] - run_cnt[1])

def enable_rnn_executor(self, net, value, forward_only):
        num_found = 0
        for op in net.Proto().op:
            if op.type.startswith("RecurrentNetwork"):
                for arg in op.arg:
                    if arg.name == 'enable_rnn_executor':
                        arg.i = value
                        num_found += 1
        # This sanity check is so that if someone changes the
        # enable_rnn_executor parameter name, the test will
        # start failing as this function will become defective.
        self.assertEqual(1 if forward_only else 2, num_found)

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