Merge pull request #124 from marty1885/apichange

Mostly fixing bugs

Author: marty1885

Etaler/Algorithms/SpatialPooler.hpp

@@ -42,7 +42,7 @@ struct ETALER_EXPORT SpatialPooler
 	size_t globalDensity() const { return global_density_; }
 
 	void setBoostingFactor(float f) { boost_factor_ = f; }
-	float boostFactor() { return boost_factor_; }
+	float boostFactor() const { return boost_factor_; }
 
 	Tensor connections() const {return connections_;}
 	Tensor permanences() const {return permanences_;}

Etaler/Core/Tensor.cpp

@@ -178,7 +178,7 @@ Tensor Tensor::view(svector<Range> ranges) const
 
 	auto resolve_index = [](intmax_t idx, intmax_t size) -> intmax_t {
 		if(idx < 0)
-			return size-idx;
+			return size+idx;
 		return idx;
 	};
 
@@ -202,22 +202,22 @@ Tensor Tensor::view(svector<Range> ranges) const
 
 		intmax_t start = r.start().value_or(0);
 		intmax_t stop = r.stop().value_or(dim_size);
-		intmax_t step = r.step().value_or(1);
+
+		intmax_t real_start = resolve_index(start, dim_size);
+		intmax_t real_stop = resolve_index(stop, dim_size);
+		intmax_t step = r.step().value_or(real_stop>real_start?1:-1);
+		intmax_t size = (std::abs(real_stop - real_start) - 1) / std::abs(step) + 1;
 
 		// Indexing validations
+		if(is_index_valid(stop, dim_size+1) == false)
+			throw EtError("Stopping index " + std::to_string(stop) + " is out of range in dimension " + std::to_string(i));
 		if(step == 0)
 			throw EtError("Error: Step size is zero in dimension " + std::to_string(i));
 		if(is_index_valid(start, dim_size) == false)
 			throw EtError("Starting index " + std::to_string(start) + " is out of range in dimension " + std::to_string(i));
-		if(is_index_valid(stop, dim_size+1) == false)
-			throw EtError("Stopping index " + std::to_string(stop) + " is out of range in dimension " + std::to_string(i));
-
-		intmax_t real_start = resolve_index(start, dim_size);
-		intmax_t real_stop = resolve_index(stop, dim_size);
-		intmax_t size = (real_stop - real_start - 1) / step + 1;
-
 		if((real_stop - real_start) * step < 0)
 			throw EtError("Step is going in the wrong direction. Will cause infinate loop");
+
 		viewed_strides[i] *= step;
 
 		offset.push_back(real_start);

Etaler/Core/Tensor.hpp

@@ -31,18 +31,18 @@ struct ETALER_EXPORT TensorIterator
 
 	using ThisIterator = TensorIterator<T>;
 	TensorIterator() = default;
-	TensorIterator(reference t, intmax_t offset = 0) : t_(&t), offset_(offset)
+	TensorIterator(reference t, intmax_t offset = 0) : t_(t), offset_(offset)
 	{static_assert(std::is_same_v<raw_value_type, Tensor>); }
-	value_type operator*() { return t_->view({offset_}); }
+	value_type operator*() { return t_.view({offset_}); }
 	// Unfortunatelly returning a pointer is not doable
-	pointer operator->() { return std::make_unique<raw_value_type>(*(*this)); }
-	bool operator==(ThisIterator rhs) const { return offset_ == rhs.offset_ && t_ == rhs.t_; }
+	pointer operator->() { return std::make_unique<raw_value_type>(this->operator*()); }
+	bool operator==(ThisIterator rhs) const { return offset_ == rhs.offset_ && t_.pimpl() == rhs.t_.pimpl(); }
 	bool operator!=(ThisIterator rhs) const { return !(*this == rhs); }
 	ThisIterator& operator++() {offset_ += 1; return *this;}
 	ThisIterator operator++(int) {ThisIterator retval = *this; ++(*this); return retval;}
 	ThisIterator& operator--() {offset_ -= 1; return *this;}
 	ThisIterator operator--(int) {ThisIterator retval = *this; --(*this); return retval;}
-	value_type* t_ = nullptr; // Using a pointer because Tensor is a incomplete type here
+	value_type t_;
 	intmax_t offset_ = 0;
 };
 
@@ -300,7 +300,12 @@ inline Tensor ravel(const Tensor& t)
 inline Tensor cellActivity(const Tensor& x, const Tensor& connections, const Tensor& permeances
 	, float connected_permeance, size_t active_threshold, bool has_unconnected_synapse=true)
 {
-	return x.backend()->cellActivity(x(), connections(), permeances(), connected_permeance, active_threshold, has_unconnected_synapse);
+	const Tensor& input = [&](){
+		if(x.dtype() == DType::Bool)
+			return x;
+		return x.cast(DType::Bool);
+	}();
+	return x.backend()->cellActivity(input(), connections(), permeances(), connected_permeance, active_threshold, has_unconnected_synapse);
 }
 
 inline void learnCorrilation(const Tensor& x, const Tensor& learn, const Tensor& connection

Etaler/Core/Views.hpp

@@ -15,14 +15,11 @@ struct Range
 {
 	Range() = default;
 	Range(intmax_t start)
-		: start_(start), stop_(start+1)
+		: start_(start), stop_(start+(start>=0?1:-1))
 	{}
 
-	Range(intmax_t start, intmax_t stop)
-		: start_(start), stop_(stop)
-	{}
-
-	Range(intmax_t start, intmax_t stop, intmax_t step)
+	Range(std::optional<intmax_t> start, intmax_t stop
+		, std::optional<intmax_t> step = std::nullopt)
 		: start_(start), stop_(stop), step_(step)
 	{}
 
@@ -48,7 +45,7 @@ inline Range range(intmax_t start, intmax_t end)
 
 inline Range range(intmax_t end)
 {
-	return Range(0, end);
+	return Range(std::nullopt, end);
 }
 
 inline Range range(intmax_t start, intmax_t stop, intmax_t step)

Etaler/Encoders/Category.hpp

@@ -34,8 +34,7 @@ std::vector<size_t> category(const Tensor& t, size_t num_categories)
 	et_assert(t.size()%num_categories == 0);
 	et_assert(t.dtype() == DType::Bool);
 
-	std::vector<uint8_t> vec(t.size());
-	t.backend()->copyToHost(t.pimpl(), vec.data());
+	std::vector<uint8_t> vec = t.toHost<uint8_t>();
 
 	std::set<size_t> categories;
 	size_t bits_per_category = vec.size()/num_categories;

docs/source/Contribution.md

@@ -27,5 +27,6 @@ If you want to develop the library it self, you are very welcomed! We are excite
 * Don't care about swarmming
 * follow the KISS (Keep it Simple Stupid) principle
 * Configuration files are evil (Looking at you NuPIC)
+* Avoid raw pointers. They are evil
 
 If you are adding a dependency to the library. Please discuss it in a relevant thread or make a new issue. For now, we are actively avoiding [Boost](https://www.boost.org/) and try to stick to STL as much as possible. Using Boost might lead to trouble later on. But we might decide use Boost later on.

tests/common_tests.cpp

@@ -212,6 +212,14 @@ TEST_CASE("Testing Tensor", "[Tensor]")
 			CHECK(realize(r).isSame(pred));
 		}
 
+		SECTION("Indexing with negative values") {
+			Tensor q = t.view({3});
+			Tensor r;
+			CHECK_NOTHROW(r = t.view({-1}));
+			CHECK(r.has_value() == true);
+			CHECK(q.isSame(r));
+		}
+
 		SECTION("View of views") {
 			Tensor t = ones({4, 4});
 			Tensor v1 = t[{3}];