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/locally_connected_op_test.py (7761B)

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

from caffe2.python import core, utils, workspace
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial

class TestLocallyConnectedOp(serial.SerializedTestCase):
    @given(N=st.integers(1, 3),
           C=st.integers(1, 3),
           H=st.integers(1, 5),
           W=st.integers(1, 5),
           M=st.integers(1, 3),
           kernel=st.integers(1, 3),
           op_name=st.sampled_from(["LC", "LC2D"]),
           order=st.sampled_from(["NCHW", "NHWC"]),
           use_bias=st.booleans(),
           **hu.gcs)
    @settings(deadline=10000)
    def test_lc_2d(
            self, N, C, H, W, M, kernel, op_name, order, use_bias, gc, dc):
        if H < kernel:
            kernel = H
        if W < kernel:
            kernel = W

assume(C == kernel * N)

op = core.CreateOperator(
            op_name,
            ["X", "W", "b"] if use_bias else ["X", "W"],
            ["Y"],
            kernels=[kernel, kernel],
            order=order,
            engine="",
        )

Y_H = H - kernel + 1
        Y_W = W - kernel + 1
        if order == "NCHW":
            X = np.random.rand(N, C, H, W).astype(np.float32) - 0.5
            W = np.random.rand(Y_H, Y_W, M, C, kernel,
                               kernel).astype(np.float32) - 0.5
        else:
            X = np.random.rand(N, H, W, C).astype(np.float32) - 0.5
            W = np.random.rand(Y_H, Y_W, M, kernel, kernel,
                               C).astype(np.float32) - 0.5
        b = np.random.rand(Y_H, Y_W, M).astype(np.float32) - 0.5
        inputs = [X, W, b] if use_bias else [X, W]

def lc_2d_nchw(X, W, b=None):
            N, C, XH, XW = X.shape
            YH, YW, M, _, KH, KW = W.shape

def conv(n, m, yh, yw):
                sum = b[yh, yw, m] if b is not None else 0
                for c in range(C):
                    for kh in range(KH):
                        for kw in range(KW):
                            hh = yh + kh
                            ww = yw + kw
                            sum += X[n, c, hh, ww] * W[yh, yw, m, c, kh, kw]
                return sum

output = np.zeros((N, M, YH, YW), dtype=np.float32)
            for n in range(N):
                for m in range(M):
                    for yh in range(YH):
                        for yw in range(YW):
                            output[n, m, yh, yw] = conv(n, m, yh, yw)
            return [output]

def lc_2d_nhwc(X, W, b=None):
            XT = utils.NHWC2NCHW(X)
            WT = np.transpose(W, [0, 1, 2, 5, 3, 4])
            output = lc_2d_nchw(XT, WT, b)
            return [utils.NCHW2NHWC(output[0])]

ref_op = lc_2d_nchw if order == "NCHW" else lc_2d_nhwc

self.assertReferenceChecks(
            device_option=gc,
            op=op,
            inputs=inputs,
            reference=ref_op,
        )
        self.assertDeviceChecks(dc, op, inputs, [0])
        for i in range(len(inputs)):
            self.assertGradientChecks(gc, op, inputs, i, [0])

@given(N=st.integers(1, 3),
           C=st.integers(1, 3),
           size=st.integers(1, 5),
           M=st.integers(1, 3),
           kernel=st.integers(1, 3),
           op_name=st.sampled_from(["LC", "LC1D"]),
           use_bias=st.booleans(),
           **hu.gcs)
    @settings(deadline=None)
    # Increased timeout from 1 second to 5 for ROCM
    def test_lc_1d(self, N, C, size, M, kernel, op_name, use_bias, gc, dc):
        if size < kernel:
            kernel = size

op = core.CreateOperator(
            op_name,
            ["X", "W", "b"] if use_bias else ["X", "W"],
            ["Y"],
            kernels=[kernel],
            order="NCHW",
            engine="",
        )

L = size - kernel + 1
        X = np.random.rand(N, C, size).astype(np.float32) - 0.5
        W = np.random.rand(L, M, C, kernel).astype(np.float32) - 0.5
        b = np.random.rand(L, M).astype(np.float32) - 0.5
        inputs = [X, W, b] if use_bias else [X, W]

def lc_1d_nchw(X, W, b=None):
            N, C, XL = X.shape
            YL, M, _, KL = W.shape

def conv(n, m, yl):
                sum = b[yl, m] if b is not None else 0
                for c in range(C):
                    for kl in range(KL):
                        ll = yl + kl
                        sum += X[n, c, ll] * W[yl, m, c, kl]
                return sum

output = np.zeros((N, M, YL), dtype=np.float32)
            for n in range(N):
                for m in range(M):
                    for yl in range(YL):
                        output[n, m, yl] = conv(n, m, yl)
            return [output]

self.assertReferenceChecks(
            device_option=gc,
            op=op,
            inputs=inputs,
            reference=lc_1d_nchw,
        )
        self.assertDeviceChecks(dc, op, inputs, [0])
        for i in range(len(inputs)):
            self.assertGradientChecks(gc, op, inputs, i, [0])

@given(N=st.integers(1, 1),
           C=st.integers(1, 1),
           T=st.integers(2, 2),
           H=st.integers(2, 2),
           W=st.integers(2, 2),
           M=st.integers(1, 1),
           kernel=st.integers(2, 2),
           op_name=st.sampled_from(["LC", "LC3D"]),
           use_bias=st.booleans(),
           **hu.gcs)
    @settings(deadline=None)
    def test_lc_3d(self, N, C, T, H, W, M, kernel, op_name, use_bias, gc, dc):
        if T < kernel:
            kernel = T
        if H < kernel:
            kernel = H
        if W < kernel:
            kernel = W

op = core.CreateOperator(
            op_name,
            ["X", "W", "b"] if use_bias else ["X", "W"],
            ["Y"],
            kernels=[kernel, kernel, kernel],
            order="NCHW",
            engine="",
        )

Y_T = T - kernel + 1
        Y_H = H - kernel + 1
        Y_W = W - kernel + 1
        X = np.random.rand(N, C, T, H, W).astype(np.float32) - 0.5
        W = np.random.rand(Y_T, Y_H, Y_W, M, C, kernel,
                           kernel, kernel).astype(np.float32) - 0.5
        b = np.random.rand(Y_T, Y_H, Y_W, M).astype(np.float32) - 0.5
        inputs = [X, W, b] if use_bias else [X, W]

def lc_3d_nchw(X, W, b=None):
            N, C, XT, XH, XW = X.shape
            YT, YH, YW, M, _, KT, KH, KW = W.shape

def conv(n, m, yt, yh, yw):
                sum = b[yt, yh, yw, m] if b is not None else 0
                for c in range(C):
                    for kt in range(KT):
                        for kh in range(KH):
                            for kw in range(KW):
                                tt = yt + kt
                                hh = yh + kh
                                ww = yw + kw
                                sum += X[n, c, tt, hh, ww] * \
                                    W[yt, yh, yw, m, c, kt, kh, kw]
                return sum

output = np.zeros((N, M, YT, YH, YW), dtype=np.float32)
            for n in range(N):
                for m in range(M):
                    for yt in range(YT):
                        for yh in range(YH):
                            for yw in range(YW):
                                output[n, m, yt, yh, yw] = conv(
                                    n, m, yt, yh, yw)
            return [output]

self.assertReferenceChecks(
            device_option=gc,
            op=op,
            inputs=inputs,
            reference=lc_3d_nchw,
        )
        self.assertDeviceChecks(dc, op, inputs, [0])
        for i in range(len(inputs)):
            self.assertGradientChecks(gc, op, inputs, i, [0])

cmd: