azai91 commented on a change in pull request #11608: [MXNET-489] MKLDNN Pool
test
URL: https://github.com/apache/incubator-mxnet/pull/11608#discussion_r202096903
##########
File path: tests/cpp/operator/mkldnn.cc
##########
@@ -1042,6 +1106,115 @@ void TestConcatOp(const OpAttrs &attrs, VerifyFunc
verify_fn,
}
}
+int CalculateWidthPoolOutput(int width, int kernel, int padding, int stride) {
+ return (width - kernel + 2 * padding) / stride + 1;
+}
+
+void TestPoolingOp(const OpAttrs &forward_attrs, const OpAttrs
&backwards_attrs) {
+ std::vector<NDArray*> inputs(forward_attrs.num_inputs);
+ std::vector<NDArray*> outputs(forward_attrs.num_outputs);
+ std::vector<NDArray*> ex_outputs(forward_attrs.num_outputs);
+
+ std::vector<NDArray*> backwards_input(backwards_attrs.num_inputs);
+ std::vector<NDArray*> backwards_outputs(backwards_attrs.num_outputs);
+ std::vector<NDArray*> backwards_ex_outputs(backwards_attrs.num_outputs);
+
+
+ std::vector<OpReqType> req(forward_attrs.num_outputs);
+ std::vector<OpReqType> back_req(backwards_attrs.num_outputs);
+ std::vector<DispatchMode> dispatches = forward_attrs.dispatches;
+
+ TestArrayShapes tas = GetTestArrayShapes();
+ std::vector<mkldnn::memory::primitive_desc> pds = tas.pds;
+
+ mxnet::op::PoolingParam param;
+ param.Init(forward_attrs.attrs.dict);
+ TShape kernel = param.kernel;
+ TShape padding = param.pad;
+ TShape stride = param.stride;
+
+ std::vector<NDArrayAttrs> in_arrs = GetTestInputArrays();
+ std::vector<std::vector<NDArrayAttrs>> out_arrs(forward_attrs.num_outputs);
+ std::vector<std::vector<NDArrayAttrs>>
ex_out_arrs(forward_attrs.num_outputs);
+
+ for (int i1 = 0; i1 < in_arrs.size(); i1++) {
+ auto in_arr = in_arrs[i1];
+
+ // can only pool only 3D and 4D inputs
+ TShape input_shape = in_arr.arr.shape();
+ if (input_shape.ndim() != kernel.ndim() + 2)
+ continue;
+
+ // skip if not default layout since memory layout must match
+ if (in_arr.arr.IsMKLDNNData())
+ continue;
+
+ std::vector<float> scale_vector(in_arr.arr.shape().ndim());
+ for (int i = 0; i < in_arr.arr.shape().ndim(); i++) {
+ if (i < 2)
+ scale_vector[i] = 1;
+ else
+ scale_vector[i] = CalculateWidthPoolOutput(
+ input_shape[i], kernel[i-2], padding[i-2], stride[i-2]) /
+ static_cast<float>(input_shape[i]);
+ }
+ for (int i = 0; i < forward_attrs.num_outputs; i++) {
+ out_arrs[i] = GetTestOutputArrays(in_arr.arr.shape(), pds, scale_vector);
+ ex_out_arrs[i] = GetTestOutputArrays(in_arr.arr.shape(), pds,
scale_vector);
+ }
+
+ for (int i = 0; i < forward_attrs.num_inputs; i++)
+ inputs[i] = &in_arr.arr;
+
+ for (size_t output_i = 0; output_i < out_arrs[0].size(); output_i++) {
+ for (int i = 0; i < forward_attrs.num_outputs; i++) {
+ req[i] = kWriteTo;
+ outputs[i] = &out_arrs[i][output_i].arr;
+ ex_outputs[i] = &ex_out_arrs[i][output_i].arr;
+ }
+ Imperative::Get()->set_is_training(true);
+
+ PrintVerifyMsg(in_arr, out_arrs[0][output_i]);
+ Imperative::Get()->InvokeOp(Context(), forward_attrs.attrs, inputs,
+ outputs, req, DispatchMode::kFCompute,
mxnet::OpStatePtr());
+ Imperative::Get()->InvokeOp(Context(), forward_attrs.attrs, inputs,
+ ex_outputs, req, DispatchMode::kFComputeEx,
mxnet::OpStatePtr());
+ Engine::Get()->WaitForAll();
+ VerifyCopyResult(outputs, ex_outputs);
+
+
+ // backwards test performed same time since output needed
+ if (backwards_attrs.num_inputs == 3) {
+ backwards_input[0] = outputs[0]; // output grad
+ backwards_input[1] = inputs[0]; // input
+ backwards_input[2] = outputs[0]; // output
+ } else if (backwards_attrs.num_inputs == 5) {
+ backwards_input[0] = outputs[0]; // output grad
+ backwards_input[1] = outputs[0]; // workspace grad
+ backwards_input[2] = inputs[0]; // input
+ backwards_input[3] = outputs[0]; // output
+ backwards_input[4] = ex_outputs[1]; // workspace
+ }
+
+ auto tmp_output = GetTestInputArrays(true)[i1];
+ auto tmp_output2 = GetTestInputArrays(true)[i1];
Review comment:
so I am using the input arrays as the output array for backprop. The issue
is that I write to them so I need a copy of the array. Copyfrom doesn't copy
the mkldnn memory I believe.
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