fix(representation): set correct output type for dot product

concrete/common/representation/intermediate.py

@@ -18,14 +18,7 @@ from ..debugging.custom_assert import assert_true
 from ..helpers import indexing_helpers
 from ..helpers.formatting_helpers import format_constant
 from ..helpers.python_helpers import catch, update_and_return_dict
-from ..values import (
-    BaseValue,
-    ClearScalar,
-    ClearTensor,
-    EncryptedScalar,
-    EncryptedTensor,
-    TensorValue,
-)
+from ..values import BaseValue, ClearTensor, EncryptedTensor, TensorValue
 
 IR_MIX_VALUES_FUNC_ARG_NAME = "mix_values_func"
 
@@ -490,11 +483,20 @@ class Dot(IntermediateNode):
                 f"Dot between vectors of shapes {lhs.shape} and {rhs.shape} is not supported",
             )
 
-        output_scalar_value = (
-            EncryptedScalar if (lhs.is_encrypted or rhs.is_encrypted) else ClearScalar
-        )
+        output_shape: Tuple[int, ...]
+        if (lhs.ndim == 1 and rhs.ndim == 1) or (lhs.ndim == 0 and rhs.ndim == 0):
+            # numpy.dot(x, y) where x and y are both vectors or both scalars
+            output_shape = ()
+        elif lhs.ndim == 1:
+            # numpy.dot(x, y) where x is a vector and y is a scalar
+            output_shape = lhs.shape
+        else:
+            # numpy.dot(x, y) where x is a scalar and y is a vector
+            output_shape = rhs.shape
 
-        self.outputs = [output_scalar_value(output_dtype)]
+        output_value = EncryptedTensor if (lhs.is_encrypted or rhs.is_encrypted) else ClearTensor
+
+        self.outputs = [output_value(output_dtype, output_shape)]
         self.evaluation_function = delegate_evaluation_function
 
     def text_for_drawing(self) -> str:

tests/numpy/test_compile.py

@@ -927,11 +927,6 @@ def test_compile_and_run_correctness__for_prog_with_tlu(
                 [0, 2],
             ],
         ),
-        # TODO: find a way to support this case
-        # https://github.com/zama-ai/concretefhe-internal/issues/837
-        #
-        # the problem is that compiler doesn't support combining scalars and tensors
-        # but they do support broadcasting, so scalars should be converted to (1,) shaped tensors
         pytest.param(
             lambda x: numpy.dot(x, 2),
             {
@@ -940,13 +935,7 @@ def test_compile_and_run_correctness__for_prog_with_tlu(
             [(numpy.random.randint(0, 2 ** 3, size=(3,)),) for _ in range(10)],
             ([2, 7, 1],),
             [4, 14, 2],
-            marks=pytest.mark.xfail(strict=True),
         ),
-        # TODO: find a way to support this case
-        # https://github.com/zama-ai/concretefhe-internal/issues/837
-        #
-        # the problem is that compiler doesn't support combining scalars and tensors
-        # but they do support broadcasting, so scalars should be converted to (1,) shaped tensors
         pytest.param(
             lambda x: numpy.dot(2, x),
             {
@@ -955,7 +944,6 @@ def test_compile_and_run_correctness__for_prog_with_tlu(
             [(numpy.random.randint(0, 2 ** 3, size=(3,)),) for _ in range(10)],
             ([2, 7, 1],),
             [4, 14, 2],
-            marks=pytest.mark.xfail(strict=True),
         ),
     ],
 )