arning regarding the dtype

ion-g-ion · Feb 7, 2024 · 1ba3fba · 1ba3fba
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diff --git a/examples/basic_tutorial.ipynb b/examples/basic_tutorial.ipynb
@@ -53,7 +53,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The TT approximation of a given tensor is $\\mathsf{x}_{i_1i_2...i_d} \\approx \\sum\\limits_{r_1,...,r_{d-1}=1}^{R_1,...,R_{d-1}} \\mathsf{g}^{(1)}_{1i_1r_1}\\cdots\\mathsf{g}^{(d)}_{r_{d-1}i_d1} $. Using the constructor `torchtt.TT()` a full tensor can be decomposed in the TT format."
+    "The TT approximation of a given tensor is $\\mathsf{x}_{i_1i_2...i_d} \\approx \\sum\\limits_{r_1,...,r_{d-1}=1}^{R_1,...,R_{d-1}} \\mathsf{g}^{(1)}_{1i_1r_1}\\cdots\\mathsf{g}^{(d)}_{r_{d-1}i_d1} $. Using the constructor `torchtt.TT()` a full tensor can be decomposed in the TT format.\n",
+    "The `dtype` of the input will be passed to the TT cores."
    ]
   },
   {

diff --git a/examples/basic_tutorial.py b/examples/basic_tutorial.py
@@ -14,7 +14,7 @@
 # We now create a 4d `torch.tensor` which we will use later
 tens_full = tn.reshape(tn.arange(32*16*8*10, dtype = tn.float64),[32,16,8,10])
 
-# The TT approximation of a given tensor is $\mathsf{x}_{i_1i_2...i_d} \approx \sum\limits_{r_1,...,r_{d-1}=1}^{R_1,...,R_{d-1}} \mathsf{g}^{(1)}_{1i_1r_1}\cdots\mathsf{g}^{(d)}_{r_{d-1}i_d1} $. Using the constructor `torchtt.TT()` a full tensor can be decomposed in the TT format.
+# The TT approximation of a given tensor is $\mathsf{x}_{i_1i_2...i_d} \approx \sum\limits_{r_1,...,r_{d-1}=1}^{R_1,...,R_{d-1}} \mathsf{g}^{(1)}_{1i_1r_1}\cdots\mathsf{g}^{(d)}_{r_{d-1}i_d1} $. Using the constructor `torchtt.TT()` a full tensor can be decomposed in the TT format. The `dtype` of the input will be passed to the TT cores.
 tens_tt = tntt.TT(tens_full)
 
 # The newly instantiated object contains the cores as a list, the mode sizes and the rank.

diff --git a/torchtt/_tt_base.py b/torchtt/_tt_base.py
@@ -83,6 +83,8 @@ def __init__(self, source, shape=None, eps=1e-10, rmax=sys.maxsize):
         This class implements basic operators such as `+,-,*,/,@,**` (add, subtract, elementwise multiplication, elementwise division, matrix vector product and Kronecker product) between TT instances.
         The `examples\` folder server as a tutorial for all the possibilities of the toolbox.
 
+        Be aware of the dtype of the inputs since it can affect the accuracy. Recommended is to work with float64.
+        
         Examples:
 
             .. code-block:: python