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added support for large tensors for Dropout operator and tests to verify support for more operators#16409

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rahul003 merged 3 commits intoapache:masterfrom
access2rohit:new_dgl_ops
Oct 18, 2019
Merged

added support for large tensors for Dropout operator and tests to verify support for more operators#16409
rahul003 merged 3 commits intoapache:masterfrom
access2rohit:new_dgl_ops

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@access2rohit access2rohit commented Oct 9, 2019 •
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Description

Tests added for following operators:
astype
cast
repeat
ceil
fix
floor
rint
round
trunk
arccos
arcsin
arctan
cos
degrees
radians
sin
tan
L2Normalization
InstanceNormalization

Checklist

Essentials

Please feel free to remove inapplicable items for your PR.

  • Changes are complete (i.e. I finished coding on this PR)
  • All changes have test coverage:
  • Unit tests are added for small changes to verify correctness (e.g. adding a new operator)
  • To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change

Testing

Will update results of test run here.

@access2rohit access2rohit force-pushed the new_dgl_ops branch 2 times, most recently from 11b23b2 to 083c6b5 Compare October 11, 2019 00:01
@access2rohit access2rohit changed the title [WIP]adding tests to verify large tensor support for more operators adding tests to verify large tensor support for more operators Oct 14, 2019
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access2rohit commented Oct 14, 2019

@mxnet-label-bot add [pr-awaiting-review]

@lanking520 lanking520 added the pr-awaiting-review PR is waiting for code review label Oct 14, 2019
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access2rohit commented Oct 14, 2019

@anirudh2290 @ChaiBapchya @zheng-da this PR is ready for review

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access2rohit commented Oct 15, 2019

test_large_array.test_gluon_embedding ... ok
test_large_array.test_ndarray_zeros ... ok
test_large_array.test_ndarray_ones ... ok
test_large_array.test_ndarray_convert ... ok
test_large_array.test_ndarray_random_uniform ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=583459780 to reproduce.
ok
test_large_array.test_ndarray_random_randint ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=1561187177 to reproduce.
ok
test_large_array.test_ndarray_random_exponential ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=488723450 to reproduce.
ok
test_large_array.test_ndarray_random_gamma ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=1246538300 to reproduce.
ok
test_large_array.test_ndarray_random_multinomial ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=279077978 to reproduce.

ok
test_large_array.test_ndarray_random_generalized_negative_binomial ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=582809580 to reproduce.
ok
test_large_array.test_ndarray_random_negative_binomial ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=1682432459 to reproduce.
ok
test_large_array.test_ndarray_random_normal ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=721628740 to reproduce.
ok
test_large_array.test_ndarray_random_poisson ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=1614267541 to reproduce.
ok
test_large_array.test_ndarray_random_randn ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=1931064888 to reproduce.
ok
test_large_array.test_ndarray_random_shuffle ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=887032379 to reproduce.
ok
test_large_array.test_ndarray_empty ... ok
test_large_array.test_elementwise ... ok
test_large_array.test_reduce ... ok
test_large_array.test_dot ... ok
test_large_array.test_FullyConnected ... ok
test_large_array.test_broadcast ... ok
test_large_array.test_clip ... ok
test_large_array.test_split ... ok
test_large_array.test_argmin ... ok
test_large_array.test_tile ... ok
test_large_array.test_take ... ok
test_large_array.test_slice ... ok
test_large_array.test_slice_assign ... ok
test_large_array.test_expand_dims ... ok
Helper function that cleans up memory by releasing it from memory pool ... ok
test_large_array.test_squeeze ... ok
test_large_array.test_broadcast_div ... ok
test_large_array.test_Dense ... ok
test_large_array.test_where ... ok
test_large_array.test_pick ... ok
test_large_array.test_depthtospace ... ok
test_large_array.test_spacetodepth ... ok
test_large_array.test_diag ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=1737100945 to reproduce.
ok
test_large_array.test_ravel_multi_index ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=1577038190 to reproduce.
ok
test_large_array.test_unravel_index ... [DEBUG] Setting test np/mx/python random seeds, use MXNET_TEST_SEED=754939684 to reproduce.
ok
test_large_array.test_transpose ... ok
test_large_array.test_swapaxes ... ok
test_large_array.test_flip ... ok

test_large_array.test_softmax ... ok
test_large_array.test_argsort ... ok
test_large_array.test_sort ... ok
test_large_array.test_topk ... ok
test_large_array.test_exponent_logarithm_operators ... ok
test_large_array.test_power_operators ... ok

test_large_array.test_sequence_mask ... ok
test_large_array.test_sequence_reverse ... ok
test_large_array.test_sequence_last ... ok
test_large_array.test_softmax_cross_entropy ... ok
test_large_array.test_index_copy ... ok
test_large_array.testSoftmaxOutput ... ok
test_large_array.test_leaky_relu ... ok
test_large_array.test_pooling ... ok
test_large_array.test_layer_norm ... ok

test_large_array.test_dropout ... ok
test_large_array.test_activation ... ok
test_large_array.test_batchnorm ... ok
test_large_array.test_add ... ok
test_large_array.test_sub ... ok
test_large_array.test_rsub ... ok
test_large_array.test_neg ... ok
test_large_array.test_mul ... ok
test_large_array.test_div ... ok
test_large_array.test_rdiv ... ok
test_large_array.test_mod ... ok
test_large_array.test_rmod ... ok
test_large_array.test_imod ... ok
test_large_array.test_pow ... ok
test_large_array.test_rpow ... ok
test_large_array.test_shape ... ok
test_large_array.test_size ... ok
test_large_array.test_copy ... ok
test_large_array.test_copy_to ... ok
test_large_array.test_zeros_like ... ok
test_large_array.test_ones_like ... ok
test_large_array.test_reshape_like ... ok
test_large_array.test_flatten ... ok
test_large_array.test_concat ... ok
test_large_array.test_stack ... ok
test_large_array.test_broadcast_axes ... ok
test_large_array.test_sum ... ok
test_large_array.test_prod ... ok
test_large_array.test_mean ... ok
test_large_array.test_min ... ok
test_large_array.test_max ... ok
test_large_array.test_norm ... ok
test_large_array.test_argmax ... ok
test_large_array.test_relu ... ok
test_large_array.test_sigmoid ... ok
test_large_array.test_log_softmax ... ok
test_large_array.test_iadd ... ok
test_large_array.test_isub ... ok
test_large_array.test_imul ... ok
test_large_array.test_idiv ... ok
test_large_array.test_eq ... ok
test_large_array.test_neq ... ok
test_large_array.test_lt ... ok
test_large_array.test_lte ... ok
test_large_array.test_gt ... ok
test_large_array.test_gte ... ok
test_large_array.test_slice_like ... ok
test_large_array.test_slice_axis ... ok
test_large_array.test_one_hot ... ok
test_large_array.test_full ... ok
test_large_array.test_astype ... ok
test_large_array.test_cast ... ok
test_large_array.test_repeat ... ok
test_large_array.test_ceil ... ok
test_large_array.test_fix ... ok
test_large_array.test_floor ... ok
test_large_array.test_rint ... ok
test_large_array.test_round ... ok
test_large_array.test_trunc ... ok
test_large_array.test_arcsin ... ok
test_large_array.test_arccos ... ok
test_large_array.test_arctan ... ok
test_large_array.test_sin ... ok
test_large_array.test_cos ... ok
test_large_array.test_tan ... ok
test_large_array.test_radians ... ok
test_large_array.test_degrees ... ok
test_large_array.test_L2Normalization ... ok
test_large_array.test_instance_norm ... ok

@access2rohit access2rohit changed the title adding tests to verify large tensor support for more operators added support for large tensors in Dropout tests to verify support for more operators Oct 16, 2019
access2rohit
access2rohit commented Oct 16, 2019
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tests/nightly/test_large_array.py
Comment on lines +1417 to +1422
def npy_instance_norm(data, gamma, beta, axis, eps=1E-5):
if axis < 0:
axis += data.ndim
broadcast_shape = [1 for _ in range(data.ndim)]
broadcast_shape[axis] = data.shape[axis]
mean = data.mean(axis=axis, keepdims=True).astype(dtype)
var = data.var(axis=axis, keepdims=True).astype(dtype)
std = np.sqrt(var + dtype(eps)).astype(dtype)
out = gamma * (data - mean) / std + \
beta
return out
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@access2rohit access2rohit Oct 16, 2019 •
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Documentation explaining operator: https://beta.mxnet.io/api/ndarray/_autogen/mxnet.ndarray.InstanceNorm.html

@ChaiBapchya ChaiBapchya mentioned this pull request Oct 16, 2019
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access2rohit commented Oct 16, 2019

test_large_array.test_rounding_ops ... ok test_large_array.test_trigonometric_ops ... ok

anirudh2290
anirudh2290 reviewed Oct 17, 2019
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is there a comma missing in the title ?

1 . added support for large tensors in Dropout
2. tests to verify support for more operators ?

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access2rohit commented Oct 17, 2019

@sxjscience @apeforest @anirudh2290 @zheng-da @pengzhao-intel This PR is ready for review

@access2rohit access2rohit changed the title added support for large tensors in Dropout tests to verify support for more operators added support for large tensors for Dropout operator and tests to verify support for more operators Oct 17, 2019
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access2rohit commented Oct 17, 2019 •
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is there a comma missing in the title ?

1 . added support for large tensors in Dropout
2. tests to verify support for more operators ?

Aah, corrected it now. Thanks for pointing that out.

anirudh2290
anirudh2290 approved these changes Oct 17, 2019
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LGTM, please add the TODO.

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access2rohit commented Oct 17, 2019

@mxnet-label-bot add [pr-awaiting-merge]

@lanking520 lanking520 added the pr-awaiting-merge Review and CI is complete. Ready to Merge label Oct 17, 2019
@rahul003 rahul003 merged commit f2ed1d4 into apache:master Oct 18, 2019
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