FM / operator

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

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

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
activation_ops_test.py	9691	0644	edit dl rm
adadelta_test.py	7932	0644	edit dl rm
adagrad_test.py	7586	0644	edit dl rm
adagrad_test_helper.py	5181	0644	edit dl rm
adam_test.py	21559	0644	edit dl rm
affine_channel_op_test.py	3784	0644	edit dl rm
alias_with_name_test.py	938	0644	edit dl rm
apmeter_test.py	2738	0644	edit dl rm
arg_ops_test.py	1917	0644	edit dl rm
assert_test.py	797	0644	edit dl rm
async_net_barrier_test.py	946	0644	edit dl rm
atomic_ops_test.py	4104	0644	edit dl rm
basic_rnn_test.py	4720	0644	edit dl rm
batch_box_cox_test.py	5080	0644	edit dl rm
batch_bucketize_op_test.py	3730	0644	edit dl rm
batch_moments_op_test.py	2795	0644	edit dl rm
batch_sparse_to_dense_op_test.py	4199	0644	edit dl rm
bbox_transform_test.py	12258	0644	edit dl rm
bisect_percentile_op_test.py	6227	0644	edit dl rm
blobs_queue_db_test.py	3240	0644	edit dl rm
boolean_mask_test.py	16389	0644	edit dl rm
boolean_unmask_test.py	1711	0644	edit dl rm
box_with_nms_limit_op_test.py	8750	0644	edit dl rm
bucketize_op_test.py	930	0644	edit dl rm
cast_op_test.py	1600	0644	edit dl rm
ceil_op_test.py	888	0644	edit dl rm
channel_backprop_stats_op_test.py	2131	0644	edit dl rm
channel_shuffle_test.py	1794	0644	edit dl rm
channel_stats_op_test.py	2639	0644	edit dl rm
checkpoint_test.py	1500	0644	edit dl rm
clip_op_test.py	1984	0644	edit dl rm
clip_tensor_op_test.py	2076	0644	edit dl rm
collect_and_distribute_fpn_rpn_proposals_op_test.py	11269	0644	edit dl rm
concat_op_cost_test.py	2858	0644	edit dl rm
concat_split_op_test.py	7266	0644	edit dl rm
conditional_test.py	995	0644	edit dl rm
conftest.py	1446	0644	edit dl rm
conv_test.py	32473	0644	edit dl rm
conv_transpose_test.py	15945	0644	edit dl rm
copy_ops_test.py	7374	0644	edit dl rm
copy_rows_to_tensor_op_test.py	2526	0644	edit dl rm
cosine_embedding_criterion_op_test.py	1953	0644	edit dl rm
counter_ops_test.py	3348	0644	edit dl rm
crf_test.py	5315	0644	edit dl rm
cross_entropy_ops_test.py	10085	0644	edit dl rm
ctc_beam_search_decoder_op_test.py	5197	0644	edit dl rm
ctc_greedy_decoder_op_test.py	4743	0644	edit dl rm
cudnn_recurrent_test.py	5817	0644	edit dl rm
dataset_ops_test.py	23847	0644	edit dl rm
data_couple_op_test.py	858	0644	edit dl rm
decay_adagrad_test.py	2694	0644	edit dl rm
deform_conv_test.py	19276	0644	edit dl rm
dense_vector_to_id_list_op_test.py	2044	0644	edit dl rm
depthwise_3x3_conv_test.py	1863	0644	edit dl rm
detectron_keypoints.py	7973	0644	edit dl rm
distance_op_test.py	4351	0644	edit dl rm
dropout_op_test.py	2971	0644	edit dl rm
duplicate_operands_test.py	734	0644	edit dl rm
elementwise_linear_op_test.py	1382	0644	edit dl rm
elementwise_logical_ops_test.py	4617	0644	edit dl rm
elementwise_ops_test.py	33354	0644	edit dl rm
elementwise_op_broadcast_test.py	17466	0644	edit dl rm
emptysample_ops_test.py	1977	0644	edit dl rm
enforce_finite_op_test.py	1286	0644	edit dl rm
ensure_clipped_test.py	1505	0644	edit dl rm
ensure_cpu_output_op_test.py	1244	0644	edit dl rm
erf_op_test.py	749	0644	edit dl rm
expand_op_test.py	2109	0644	edit dl rm
fc_operator_test.py	3720	0644	edit dl rm
feature_maps_ops_test.py	21492	0644	edit dl rm
filler_ops_test.py	8476	0644	edit dl rm
find_op_test.py	1316	0644	edit dl rm
flatten_op_test.py	922	0644	edit dl rm
flexible_top_k_test.py	2609	0644	edit dl rm
floor_op_test.py	894	0644	edit dl rm
fused_nbit_rowwise_conversion_ops_test.py	14077	0644	edit dl rm
fused_nbit_rowwise_test_helper.py	2693	0644	edit dl rm
gather_ops_test.py	9216	0644	edit dl rm
gather_ranges_op_test.py	9125	0644	edit dl rm
given_tensor_byte_string_to_uint8_fill_op_test.py	1392	0644	edit dl rm
given_tensor_fill_op_test.py	1503	0644	edit dl rm
glu_op_test.py	1212	0644	edit dl rm
group_conv_test.py	2870	0644	edit dl rm
group_norm_op_test.py	5252	0644	edit dl rm
gru_test.py	12932	0644	edit dl rm
heatmap_max_keypoint_op_test.py	4770	0644	edit dl rm
histogram_test.py	3097	0644	edit dl rm
hsm_test.py	9456	0644	edit dl rm
hyperbolic_ops_test.py	1472	0644	edit dl rm
im2col_col2im_test.py	4311	0644	edit dl rm
image_input_op_test.py	17345	0644	edit dl rm
index_hash_ops_test.py	2885	0644	edit dl rm
index_ops_test.py	4597	0644	edit dl rm
instance_norm_test.py	9917	0644	edit dl rm
integral_image_ops_test.py	3419	0644	edit dl rm
jsd_ops_test.py	1044	0644	edit dl rm
key_split_ops_test.py	1289	0644	edit dl rm
lars_test.py	1354	0644	edit dl rm
layer_norm_op_test.py	14983	0644	edit dl rm
leaky_relu_test.py	5639	0644	edit dl rm
learning_rate_adaption_op_test.py	2837	0644	edit dl rm
learning_rate_op_test.py	8652	0644	edit dl rm
lengths_pad_op_test.py	1625	0644	edit dl rm
lengths_reducer_fused_nbit_rowwise_ops_test.py	15495	0644	edit dl rm
lengths_tile_op_test.py	1332	0644	edit dl rm
lengths_top_k_ops_test.py	2371	0644	edit dl rm
length_split_op_test.py	4868	0644	edit dl rm
listwise_l2r_operator_test.py	8740	0644	edit dl rm
load_save_test.py	33241	0644	edit dl rm
locally_connected_op_test.py	7761	0644	edit dl rm
loss_ops_test.py	902	0644	edit dl rm
lpnorm_op_test.py	2725	0644	edit dl rm
map_ops_test.py	2249	0644	edit dl rm
margin_ranking_criterion_op_test.py	1816	0644	edit dl rm
math_ops_test.py	1603	0644	edit dl rm
matmul_op_test.py	10096	0644	edit dl rm
mean_op_test.py	1469	0644	edit dl rm
merge_id_lists_op_test.py	2989	0644	edit dl rm
mkl_conv_op_test.py	1547	0644	edit dl rm
mkl_packed_fc_op_test.py	2647	0644	edit dl rm
mod_op_test.py	1459	0644	edit dl rm
moments_op_test.py	1722	0644	edit dl rm
momentum_sgd_test.py	6480	0644	edit dl rm
mpi_test.py	8154	0644	edit dl rm
mul_gradient_benchmark.py	1509	0644	edit dl rm
negate_gradient_op_test.py	1518	0644	edit dl rm
ngram_ops_test.py	2327	0644	edit dl rm
normalize_op_test.py	1679	0644	edit dl rm
numpy_tile_op_test.py	1924	0644	edit dl rm
one_hot_ops_test.py	7478	0644	edit dl rm
onnx_while_test.py	3070	0644	edit dl rm
order_switch_test.py	1306	0644	edit dl rm
pack_ops_test.py	12634	0644	edit dl rm
pack_rnn_sequence_op_test.py	2891	0644	edit dl rm
pad_test.py	1377	0644	edit dl rm
partition_ops_test.py	6838	0644	edit dl rm
percentile_op_test.py	4427	0644	edit dl rm
piecewise_linear_transform_test.py	6187	0644	edit dl rm
pooling_test.py	16508	0644	edit dl rm
prepend_dim_test.py	1505	0644	edit dl rm
python_op_test.py	1312	0644	edit dl rm
quantile_test.py	3276	0644	edit dl rm
rand_quantization_op_speed_test.py	3128	0644	edit dl rm
rank_loss_operator_test.py	5752	0644	edit dl rm
rebatching_queue_test.py	9047	0644	edit dl rm
record_queue_test.py	3125	0644	edit dl rm
recurrent_network_test.py	14048	0644	edit dl rm
recurrent_net_executor_test.py	10922	0644	edit dl rm
reduce_ops_test.py	17341	0644	edit dl rm
reduction_ops_test.py	4664	0644	edit dl rm
reshape_ops_test.py	8211	0644	edit dl rm
resize_op_test.py	9417	0644	edit dl rm
rmac_regions_op_test.py	3178	0644	edit dl rm
rms_norm_op_test.py	1325	0644	edit dl rm
rnn_cell_test.py	59707	0644	edit dl rm
roi_align_rotated_op_test.py	7567	0644	edit dl rm
rowwise_counter_test.py	2205	0644	edit dl rm
scale_op_test.py	2177	0644	edit dl rm
segment_ops_test.py	25745	0644	edit dl rm
self_binning_histogram_test.py	12915	0644	edit dl rm
selu_op_test.py	3232	0644	edit dl rm
sequence_ops_test.py	16000	0644	edit dl rm
shape_inference_test.py	25708	0644	edit dl rm
sinusoid_position_encoding_op_test.py	2308	0644	edit dl rm
softmax_ops_test.py	23685	0644	edit dl rm
softplus_op_test.py	516	0644	edit dl rm
sparse_dropout_with_replacement_op_test.py	2885	0644	edit dl rm
sparse_gradient_checker_test.py	1294	0644	edit dl rm
sparse_itemwise_dropout_with_replacement_op_test.py	2913	0644	edit dl rm
sparse_lengths_sum_benchmark.py	4159	0644	edit dl rm
sparse_lp_regularizer_test.py	2553	0644	edit dl rm
sparse_normalize_test.py	3136	0644	edit dl rm
sparse_ops_test.py	3469	0644	edit dl rm
sparse_to_dense_mask_op_test.py	3693	0644	edit dl rm
spatial_bn_op_test.py	20182	0644	edit dl rm
specialized_segment_ops_test.py	11775	0644	edit dl rm
split_op_cost_test.py	8645	0644	edit dl rm
square_root_divide_op_test.py	2179	0644	edit dl rm
stats_ops_test.py	1789	0644	edit dl rm
stats_put_ops_test.py	6596	0644	edit dl rm
storm_test.py	6507	0644	edit dl rm
string_ops_test.py	4154	0644	edit dl rm
text_file_reader_test.py	2517	0644	edit dl rm
thresholded_relu_op_test.py	2323	0644	edit dl rm
tile_op_test.py	3887	0644	edit dl rm
top_k_test.py	9113	0644	edit dl rm
torch_integration_test.py	39941	0644	edit dl rm
transpose_op_test.py	2722	0644	edit dl rm
trigonometric_op_test.py	1715	0644	edit dl rm
unique_ops_test.py	2255	0644	edit dl rm
unique_uniform_fill_op_test.py	1335	0644	edit dl rm
unsafe_coalesce_test.py	2940	0644	edit dl rm
upsample_op_test.py	7308	0644	edit dl rm
utility_ops_test.py	15054	0644	edit dl rm
video_input_op_test.py	10503	0644	edit dl rm
weighted_multi_sample_test.py	1997	0644	edit dl rm
weighted_sample_test.py	2739	0644	edit dl rm
weighted_sum_test.py	3052	0644	edit dl rm
weight_scale_test.py	2057	0644	edit dl rm
wngrad_test.py	8279	0644	edit dl rm
__init__.py	0	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/caffe2/python/operator_test/hsm_test.py (9456B)

from hypothesis import given, settings
import numpy as np
import unittest

from caffe2.proto import caffe2_pb2, hsm_pb2
from caffe2.python import workspace, core, gradient_checker
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.hsm_util as hsmu

# User inputs tree using protobuf file or, in this case, python utils
# The hierarchy in this test looks as shown below. Note that the final subtrees
# (with word_ids as leaves) have been collapsed for visualization
#           *
#         /  \
#        *    5,6,7,8
#       / \
#  0,1,2   3,4
tree = hsm_pb2.TreeProto()
words = [[0, 1, 2], [3, 4], [5, 6, 7, 8]]
node1 = hsmu.create_node_with_words(words[0], "node1")
node2 = hsmu.create_node_with_words(words[1], "node2")
node3 = hsmu.create_node_with_words(words[2], "node3")
node4 = hsmu.create_node_with_nodes([node1, node2], "node4")
node = hsmu.create_node_with_nodes([node4, node3], "node5")
tree.root_node.MergeFrom(node)

# structure:
# node5: [0, 2, ["node4", "node3"]] # offset, length, "node4, node3"
# node4: [2, 2, ["node1", "node2"]]
# node1: [4, 3, [0, 1 ,2]]
# node2: [7, 2, [3, 4]
# node3: [9, 4, [5, 6, 7, 8]
struct = [[0, 2, ["node4", "node3"], "node5"],
            [2, 2, ["node1", "node2"], "node4"],
            [4, 3, [0, 1, 2], "node1"],
            [7, 2, [3, 4], "node2"],
            [9, 4, [5, 6, 7, 8], "node3"]]

# Internal util to translate input tree to list of (word_id,path). serialized
# hierarchy is passed into the operator_def as a string argument,
hierarchy_proto = hsmu.create_hierarchy(tree)
arg = caffe2_pb2.Argument()
arg.name = "hierarchy"
arg.s = hierarchy_proto.SerializeToString()

beam = 5
args_search = []
arg_search = caffe2_pb2.Argument()
arg_search.name = "tree"
arg_search.s = tree.SerializeToString()
args_search.append(arg_search)
arg_search = caffe2_pb2.Argument()
arg_search.name = "beam"
arg_search.f = beam
args_search.append(arg_search)

class TestHsm(hu.HypothesisTestCase):
    def test_hsm_search(self):
        samples = 10
        dim_in = 5
        X = np.random.rand(samples, dim_in).astype(np.float32) - 0.5
        w = np.random.rand(hierarchy_proto.size, dim_in) \
            .astype(np.float32) - 0.5
        b = np.random.rand(hierarchy_proto.size).astype(np.float32) - 0.5
        labels = np.array([np.random.randint(0, 8) for i in range(samples)]) \
            .astype(np.int32)

workspace.GlobalInit(['caffe2'])
        workspace.FeedBlob("data", X)
        workspace.FeedBlob("weights", w)
        workspace.FeedBlob("bias", b)
        workspace.FeedBlob("labels", labels)
        op = core.CreateOperator(
            'HSoftmaxSearch',
            ['data', 'weights', 'bias'],
            ['names', 'scores'],
            'HSoftmaxSearch',
            arg=args_search)
        workspace.RunOperatorOnce(op)
        names = workspace.FetchBlob('names')
        scores = workspace.FetchBlob('scores')

def simulation_hsm_search():
            names = []
            scores = []
            for line in struct:
                s, e = line[0], line[0] + line[1]
                score = np.dot(X, w[s:e].transpose()) + b[s:e]
                score = np.exp(score - np.max(score, axis=1, keepdims=True))
                score /= score.sum(axis=1, keepdims=True)
                score = -np.log(score)

score = score.transpose()
                idx = -1
                for j, n in enumerate(names):
                    if n == line[3]:
                        idx = j
                        score += scores[j]
                if idx == -1:
                    score[score > beam] = np.inf
                else:
                    score[score - scores[idx] > beam] = np.inf

for i, name in enumerate(line[2]):
                    scores.append(score[i])
                    names.append(name)
            scores = np.vstack(scores)
            return names, scores.transpose()

p_names, p_scores = simulation_hsm_search()
        idx = np.argsort(p_scores, axis=1)
        p_scores = np.sort(p_scores, axis=1)
        p_names = np.array(p_names)[idx]
        for i in range(names.shape[0]):
            for j in range(names.shape[1]):
                if names[i][j]:
                    self.assertEquals(
                        names[i][j], p_names[i][j].item().encode('utf-8'))
                    self.assertAlmostEqual(
                        scores[i][j], p_scores[i][j], delta=0.001)

def test_hsm_run_once(self):
        workspace.GlobalInit(['caffe2'])
        workspace.FeedBlob("data",
                           np.random.randn(1000, 100).astype(np.float32))
        workspace.FeedBlob("weights",
                           np.random.randn(1000, 100).astype(np.float32))
        workspace.FeedBlob("bias", np.random.randn(1000).astype(np.float32))
        workspace.FeedBlob("labels", np.random.rand(1000).astype(np.int32) * 9)
        op = core.CreateOperator(
            'HSoftmax',
            ['data', 'weights', 'bias', 'labels'],
            ['output', 'intermediate_output'],
            'HSoftmax',
            arg=[arg])
        self.assertTrue(workspace.RunOperatorOnce(op))

# Test to check value of sum of squared losses in forward pass for given
    # input
    def test_hsm_forward(self):
        cpu_device_option = caffe2_pb2.DeviceOption()
        grad_checker = gradient_checker.GradientChecker(
            0.01, 0.05, cpu_device_option, "default")
        samples = 9
        dim_in = 5
        X = np.zeros((samples, dim_in)).astype(np.float32) + 1
        w = np.zeros((hierarchy_proto.size, dim_in)).astype(np.float32) + 1
        b = np.array([i for i in range(hierarchy_proto.size)])\
            .astype(np.float32)
        labels = np.array([i for i in range(samples)]).astype(np.int32)

workspace.GlobalInit(['caffe2'])
        workspace.FeedBlob("data", X)
        workspace.FeedBlob("weights", w)
        workspace.FeedBlob("bias", b)
        workspace.FeedBlob("labels", labels)

op = core.CreateOperator(
            'HSoftmax',
            ['data', 'weights', 'bias', 'labels'],
            ['output', 'intermediate_output'],
            'HSoftmax',
            arg=[arg])
        grad_ops, g_input = core.GradientRegistry.GetGradientForOp(
            op, [s + '_grad' for s in op.output])

loss, _ = grad_checker.GetLossAndGrad(
            op, grad_ops, [X, w, b, labels], op.input, 0, g_input[0], [0]
        )
        self.assertAlmostEqual(loss, 44.269, delta=0.001)

# Test to compare gradient calculated using the gradient operator and the
    # symmetric derivative calculated using Euler Method
    # TODO : convert to both cpu and gpu test when ready.
    @given(**hu.gcs_cpu_only)
    @settings(deadline=10000)
    def test_hsm_gradient(self, gc, dc):
        samples = 10
        dim_in = 5
        X = np.random.rand(samples, dim_in).astype(np.float32) - 0.5
        w = np.random.rand(hierarchy_proto.size, dim_in) \
            .astype(np.float32) - 0.5
        b = np.random.rand(hierarchy_proto.size).astype(np.float32) - 0.5
        labels = np.array([np.random.randint(0, 8) for i in range(samples)]) \
            .astype(np.int32)

workspace.GlobalInit(['caffe2'])
        workspace.FeedBlob("data", X)
        workspace.FeedBlob("weights", w)
        workspace.FeedBlob("bias", b)
        workspace.FeedBlob("labels", labels)

op = core.CreateOperator(
            'HSoftmax',
            ['data', 'weights', 'bias', 'labels'],
            ['output', 'intermediate_output'],
            'HSoftmax',
            arg=[arg])

self.assertDeviceChecks(dc, op, [X, w, b, labels], [0])

for i in range(3):
            self.assertGradientChecks(gc, op, [X, w, b, labels], i, [0])

def test_huffman_tree_hierarchy(self):
        workspace.GlobalInit(['caffe2'])
        labelSet = list(range(0, 6))
        counts = [1, 2, 3, 4, 5, 6]
        labels = sum([[l] * c for (l, c) in zip(labelSet, counts)], [])
        Y = np.array(labels).astype(np.int64)
        workspace.FeedBlob("labels", Y)
        arg = caffe2_pb2.Argument()
        arg.name = 'num_classes'
        arg.i = 6
        op = core.CreateOperator(
            'HuffmanTreeHierarchy',
            ['labels'],
            ['huffman_tree'],
            'HuffmanTreeHierarchy',
            arg=[arg])
        workspace.RunOperatorOnce(op)
        huffmanTreeOutput = workspace.FetchBlob('huffman_tree')
        treeOutput = hsm_pb2.TreeProto()
        treeOutput.ParseFromString(huffmanTreeOutput[0])
        treePathOutput = hsmu.create_hierarchy(treeOutput)

label_to_path = {}
        for path in treePathOutput.paths:
            label_to_path[path.word_id] = path

def checkPath(label, indices, code):
            path = label_to_path[label]
            self.assertEqual(len(path.path_nodes), len(code))
            self.assertEqual(len(path.path_nodes), len(code))
            for path_node, index, target in \
                    zip(path.path_nodes, indices, code):
                self.assertEqual(path_node.index, index)
                self.assertEqual(path_node.target, target)
        checkPath(0, [0, 4, 6, 8], [1, 0, 0, 0])
        checkPath(1, [0, 4, 6, 8], [1, 0, 0, 1])
        checkPath(2, [0, 4, 6], [1, 0, 1])
        checkPath(3, [0, 2], [0, 0])
        checkPath(4, [0, 2], [0, 1])
        checkPath(5, [0, 4], [1, 1])

if __name__ == '__main__':
    unittest.main()

cmd: