fix: comments

src/concrete/ml/quantization/base_quantized_op.py

@@ -725,10 +725,18 @@ def calibrate(self, *inputs: Union[QuantizedArray, numpy.ndarray]) -> numpy.ndar
         if isinstance(raw_result, RawOpOutput):
             return raw_result
 
-        supports_analytical_quant = all(
+        # If the caller passes only QuantizedArray it means
+        # that they are asking to quantized using analytical
+        # formulas
+        requested_analytical_quant = all(
             isinstance(qv, QuantizedArray) for qv in inputs
         ) and isinstance(self, QuantizedMixingOp)
-        if supports_analytical_quant:
+        if requested_analytical_quant:
+            assert_true(
+                self.supported_by_linear_backend(),
+                "Calibration using QuantizedArray is only possible"
+                " for operations that can calibrate analytically",
+            )
             q_prepared_inputs = self._prepare_inputs_with_constants(
                 *inputs, calibrate=False, quantize_actual_values=True
             )

src/concrete/ml/quantization/quantized_ops.py

@@ -205,12 +205,12 @@ def q_impl(
         # Using snake case here to please the Python format, the original attrs don't have the '_'
         # Use default false so we also support MatMul impl, MatMul does not have these flags
         transpose_inputs1 = attrs.get("transA", False)
-        transpose_inputs2 = attrs.get("transB", False)
-
         with tag(self.op_instance_name + ".input"):
             input1_q_values = (
                 numpy.transpose(q_input1.qvalues) if transpose_inputs1 else q_input1.qvalues
             )
+
+        transpose_inputs2 = attrs.get("transB", False)
         input2_q_values = (
             numpy.transpose(q_input2.qvalues) if transpose_inputs2 else q_input2.qvalues
         )