nikudyshko opened a new issue #18668:
URL: https://github.com/apache/incubator-mxnet/issues/18668
## Description
While creating a neural network with MXNet cpp-api, if set `dtype` of know
args to `1 (corresponds float64)`, `InferArgsMap` will not transfer this type
to infered args. This causes error, when creating Executor.
### Error Message
[22:30:58]
C:\Users\UserName\Desktop\neural_nets\Mark1\Mark1\mxnet\include\dmlc\logging.h:429:
[22:30:58]
C:\Users\UserName\Desktop\neural_nets\Mark1\Mark1\mxnet\include\mxnet-cpp\executor.hpp:85:
Check failed: MXExecutorBindEX(symbol.GetHandle(), context.GetDeviceType(),
context.GetDeviceId(), group_to_ctx.size(), map_keys.data(), dev_types.data(),
dev_ids.data(), arg_handles.size(), arg_handles.data(), grad_handles.data(),
grad_reqs_uint.data(), aux_handles.size(), aux_handles.data(),
shared_exec_handle, &handle_) == 0 (-1 vs. 0) :
## To Reproduce
```cpp
#include <chrono>
#include "mxnet-cpp/MxNetCpp.h"
using namespace mxnet::cpp;
Symbol mlp(const std::vector<int>& layers) {
auto x = Symbol::Variable("X");
auto label = Symbol::Variable("label");
std::vector<Symbol> weights(layers.size());
std::vector<Symbol> biases(layers.size());
std::vector<Symbol> outputs(layers.size());
for (size_t i = 0; i < layers.size(); ++i) {
weights[i] = Symbol::Variable("w" + std::to_string(i));
biases[i] = Symbol::Variable("b" + std::to_string(i));
Symbol fc = FullyConnected(
i == 0 ? x : outputs[i - 1], // data
weights[i],
biases[i],
layers[i]);
outputs[i] = i == layers.size() - 1 ? fc : Activation(fc,
ActivationActType::kRelu);
}
return SoftmaxOutput(outputs.back(), label);
}
int main()
{
const int image_size = 28;
const std::vector<int> layers{ 128, 64, 10 };
const int batch_size = 100;
const int max_epoch = 10;
const float learning_rate = 0.1;
const float weight_decay = 1e-2;
auto net = mlp(layers);
Context ctx = Context::cpu(); // Use CPU for training
std::map<std::string, NDArray> args;
args["X"] = NDArray(Shape(batch_size, image_size * image_size), ctx,
true, 1); // 1 should correspond to float64
args["label"] = NDArray(Shape(batch_size), ctx, true, 1); // 1 should
correspond to float64
// Let MXNet infer shapes other parameters such as weights
net.InferArgsMap(ctx, &args, args);
for (auto& arg : args)
std::cout << arg.first << ' ' << arg.second.GetDType() << '\n';
// Output here:
// X 1
// b0 0
// b1 0
// b2 0
// label 1
// w0 0
// w1 0
// w2 0
// All 0 should be 1
// Create executor by binding parameters to the model
auto* exec = net.SimpleBind(ctx, args); // Error here
return 0;
}
```
### Steps to reproduce
Just compile and run the code above
## What have you tried to solve it?
I've tried to add `dtype`-infering to the code of `InferArgsMap`. This
allowed me to create a network, but than an had been thrown on args
destruction.
## Environment
Win10 64-bit, VS2019, MXNet
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