lib/torch/tensor.rb in torch-rb-0.1.4 vs lib/torch/tensor.rb in torch-rb-0.1.5

@@ -3,16 +3,12 @@
     include Comparable
     include Inspector
 
     alias_method :requires_grad?, :requires_grad
 
-    def self.new(*size)
-      if size.length == 1 && size.first.is_a?(Tensor)
-        size.first
-      else
-        Torch.empty(*size)
-      end
+    def self.new(*args)
+      FloatTensor.new(*args)
     end
 
     def dtype
       dtype = ENUM_TO_DTYPE[_dtype]
       raise Error, "Unknown type: #{_dtype}" unless dtype
@@ -26,22 +22,22 @@
     def to_s
       inspect
     end
 
     def to_a
-      reshape_arr(_data, shape)
+      reshape_arr(_flat_data, shape)
     end
 
     # TODO support dtype
     def to(device, non_blocking: false, copy: false)
       device = Device.new(device) if device.is_a?(String)
       _to(device, _dtype, non_blocking, copy)
     end
 
     def size(dim = nil)
       if dim
-        _size(dim)
+        _size_int(dim)
       else
         shape
       end
     end
 
@@ -55,11 +51,11 @@
 
     def item
       if numel != 1
         raise Error, "only one element tensors can be converted to Ruby scalars"
       end
-      _data.first
+      _flat_data.first
     end
 
     # unsure if this is correct
     def new
       Torch.empty(0, dtype: dtype)
@@ -71,11 +67,11 @@
 
     # TODO read directly from memory
     def numo
       cls = Torch._dtype_to_numo[dtype]
       raise Error, "Cannot convert #{dtype} to Numo" unless cls
-      cls.cast(_data).reshape(*shape)
+      cls.cast(_flat_data).reshape(*shape)
     end
 
     def new_ones(*size, **options)
       Torch.ones_like(Torch.empty(*size), **options)
     end
@@ -88,38 +84,42 @@
       enum = DTYPE_TO_ENUM[dtype]
       raise Error, "Unknown type: #{dtype}" unless enum
       _type(enum)
     end
 
+    # start temp operations
+
     def add!(value = 1, other)
       if other.is_a?(Numeric)
-        _add_scalar!(other * value)
+        _add__scalar(other, value)
       else
         # need to use alpha for sparse tensors instead of multiplying
-        _add_alpha!(other, value)
+        _add__tensor(other, value)
       end
     end
 
     def mul!(other)
       if other.is_a?(Numeric)
-        _mul_scalar!(other)
+        _mul__scalar(other)
       else
-        _mul!(other)
+        _mul__tensor(other)
       end
     end
 
     # operations
-    %w(abs add argmax div dot eq exp gt log log_softmax lt matmul max mean min mul neg norm num numel pow relu remainder reshape sign softmax sqrt sub sum unsqueeze topk).each do |op|
+    %w(log_softmax mean softmax sum topk).each do |op|
       define_method(op) do |*args, **options, &block|
         if options.any?
           Torch.send(op, self, *args, **options, &block)
         else
           Torch.send(op, self, *args, &block)
         end
       end
     end
 
+    # end temp operations
+
     def +(other)
       add(other)
     end
 
     def -(other)
@@ -154,15 +154,15 @@
     def [](*indexes)
       result = self
       dim = 0
       indexes.each do |index|
         if index.is_a?(Numeric)
-          result = result._select(dim, index)
+          result = result._select_int(dim, index)
         elsif index.is_a?(Range)
           finish = index.end
           finish += 1 unless index.exclude_end?
-          result = result._slice(dim, index.begin, finish, 1)
+          result = result._slice_tensor(dim, index.begin, finish, 1)
           dim += 1
         elsif index.nil?
           result = result.unsqueeze(dim)
           dim += 1
         elsif index == true
@@ -181,14 +181,14 @@
       raise ArgumentError, "Tensor does not support deleting items" if value.nil?
 
       value = Torch.tensor(value) unless value.is_a?(Tensor)
 
       if index.is_a?(Numeric)
-        copy_to(_select(0, index), value)
+        copy_to(_select_int(0, index), value)
       elsif index.is_a?(Range)
         finish = index.end
         finish += 1 unless index.exclude_end?
-        copy_to(_slice(0, index.begin, finish, 1), value)
+        copy_to(_slice_tensor(0, index.begin, finish, 1), value)
       else
         raise Error, "Unsupported index type: #{index.class.name}"
       end
     end