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haoj pushed a commit to branch numpy
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
commit 24a14b3d46bf95f1ab1deac1767133893cc61523
Author: Jake Lee <gstu1...@gmail.com>
AuthorDate: Thu Jul 11 20:51:32 2019 -0700
fix memory override bug in multinomial (#15397)
---
src/operator/numpy/random/np_multinomial_op.h | 22 +++++++++++-----------
tests/python/unittest/test_numpy_ndarray.py | 10 ++++++++++
2 files changed, 21 insertions(+), 11 deletions(-)
diff --git a/src/operator/numpy/random/np_multinomial_op.h
b/src/operator/numpy/random/np_multinomial_op.h
index 39515b4..7115f27 100644
--- a/src/operator/numpy/random/np_multinomial_op.h
+++ b/src/operator/numpy/random/np_multinomial_op.h
@@ -105,7 +105,7 @@ struct multinomial_kernel {
const int num_exp,
const int prob_length,
DType* pvals,
- float* uniform,
+ double* uniform,
int64_t* out) {
for (int j = 0; j < num_exp; ++j) {
DType loc = static_cast<DType>(uniform[i * num_exp + j]);
@@ -145,20 +145,20 @@ void NumpyMultinomialForward(const nnvm::NodeAttrs& attrs,
int num_output = outputs[0].Size() / prob_length;
int num_exp = param.n;
Stream<xpu> *s = ctx.get_stream<xpu>();
- Random<xpu, float> *prnd = ctx.requested[0].get_random<xpu, float>(s);
- Tensor<xpu, 1, float> uniform =
- ctx.requested[1].get_space_typed<xpu, 1, float>(Shape1(num_output *
param.n), s);
- prnd->SampleUniform(&uniform, 0, 1);
+ Random<xpu, double> *prnd = ctx.requested[0].get_random<xpu, double>(s);
+ size_t temp_space_ = (param.pvals.has_value())
+ ? num_output * param.n + prob_length : num_output *
param.n;
+ Tensor<xpu, 1, double> temp_tensor =
+ ctx.requested[1].get_space_typed<xpu, 1, double>(Shape1(temp_space_), s);
+ prnd->SampleUniform(&temp_tensor, 0, 1);
// set zero for the outputs
Kernel<set_zero, xpu>::Launch(s, outputs[0].Size(),
outputs[0].dptr<int64_t>());
-
if (param.pvals.has_value()) {
// create a tensor to copy the param.pvals tuple to avoid
// error: calling a __host__ function from a __host__ __device__ function
is not allowed
- Tensor<xpu, 1, double> pvals =
- ctx.requested[1].get_space_typed<xpu, 1, double>(Shape1(prob_length), s);
- double* pvals_ = pvals.dptr_;
+ // reuse the uniform temp space to create pval tensor
+ double* pvals_ = temp_tensor.dptr_ + num_output * param.n;
// check if sum of input(pvals) > 1.0
double sum = 0.0;
for (int i = 0; i < prob_length; ++i) {
@@ -169,7 +169,7 @@ void NumpyMultinomialForward(const nnvm::NodeAttrs& attrs,
<< "sum(pvals[:-1]) > 1.0";
}
Kernel<multinomial_kernel, xpu>::Launch(
- s, num_output, num_exp, prob_length, pvals_, uniform.dptr_,
outputs[0].dptr<int64_t>());
+ s, num_output, num_exp, prob_length, pvals_, temp_tensor.dptr_,
outputs[0].dptr<int64_t>());
} else {
MSHADOW_TYPE_SWITCH(inputs[0].type_flag_, DType, {
// check if sum of input(pvals) > 1.0
@@ -182,7 +182,7 @@ void NumpyMultinomialForward(const nnvm::NodeAttrs& attrs,
}
Kernel<multinomial_kernel, xpu>::Launch(
s, num_output, num_exp, prob_length,
- inputs[0].dptr<DType>(), uniform.dptr_, outputs[0].dptr<int64_t>());
+ inputs[0].dptr<DType>(), temp_tensor.dptr_,
outputs[0].dptr<int64_t>());
});
}
}
diff --git a/tests/python/unittest/test_numpy_ndarray.py
b/tests/python/unittest/test_numpy_ndarray.py
index c5a9279..887bb9a 100644
--- a/tests/python/unittest/test_numpy_ndarray.py
+++ b/tests/python/unittest/test_numpy_ndarray.py
@@ -712,6 +712,16 @@ def test_np_multinomial():
for size in sizes:
freq = mx.np.random.multinomial(experiements, pvals,
size=size).asnumpy()
assert freq.size == 0
+ # test small experiment for github issue
+ # https://github.com/apache/incubator-mxnet/issues/15383
+ small_exp, total_exp = 20, 10000
+ for pvals in pvals_list:
+ x = np.random.multinomial(small_exp, pvals)
+ for i in range(total_exp // small_exp):
+ x = x + np.random.multinomial(20, pvals)
+ freq = (x.asnumpy() / _np.float32(total_exp)).reshape((-1, len(pvals)))
+ for i in range(freq.shape[0]):
+ mx.test_utils.assert_almost_equal(freq[i, :], pvals, rtol=0.20,
atol=1e-1)
if __name__ == '__main__':
