feat(frontend-python): enable multi precision and multi parameters by default

compilers/concrete-compiler/compiler/lib/Conversion/FHETensorOpsToLinalg/TensorOpsToLinalg.cpp

@@ -1678,6 +1678,21 @@ mlir::LogicalResult createGroupedConv2D(
   return mlir::success();
 }
 
+bool isZeroConstant(mlir::Value value) {
+  auto cst =
+      mlir::dyn_cast_or_null<mlir::arith::ConstantOp>(value.getDefiningOp());
+  if (cst == nullptr)
+    return false;
+  auto values = cst->getAttrOfType<mlir::DenseIntElementsAttr>("value");
+  if (values == nullptr)
+    return false;
+  for (auto v : values) {
+    if (v != 0)
+      return false;
+  }
+  return true;
+}
+
 /// This rewrite pattern transforms any instance of operators
 /// `FHELinalg.conv2d` to one or multiple instances of
 /// `linalg.conv_2d_nchw_fchw`. The transformation consists of padding the input
@@ -1767,14 +1782,13 @@ struct FHELinalgConv2dToLinalgConv2d
                                                  .cast<mlir::RankedTensorType>()
                                                  .getShape(),
                                              inputElementType));
+    forwardOptimizerID(conv2dOp, initTensor.getDefiningOp());
     // Since linalg doesn't support a bias in the conv operation, we
     // initialize the output tensor to the bias values, so that conv results
     // get accumulated to it
     mlir::Value bias = conv2dOp.getBias(); /* optional of shape: Filters */
-    mlir::Value biasInitTensor;
-    if (!bias) { // no bias was used
-      biasInitTensor = initTensor;
-    } else {
+    mlir::Value biasInitTensor = initTensor;
+    if (bias && !isZeroConstant(bias)) {
       // Fill the output tensor with bias values
       auto resultRank =
           initTensor.getType().cast<mlir::RankedTensorType>().getRank();

compilers/concrete-compiler/compiler/tests/check_tests/BugReport/bug_report_483.mlir

@@ -0,0 +1,7 @@
+// RUN: concretecompiler --action=dump-llvm-ir --optimizer-strategy=dag-multi %s
+func.func @main(%arg0: tensor<1x1x4x4x!FHE.eint<4>>) -> tensor<1x1x2x2x!FHE.eint<4>> {
+  %cst = arith.constant dense<[[[[2, 0], [3, 1]]]]> : tensor<1x1x2x2xi5>
+  %cst_0 = arith.constant dense<0> : tensor<1xi5>
+  %0 = "FHELinalg.conv2d"(%arg0, %cst, %cst_0) {dilations = dense<1> : tensor<2xi64>, group = 1 : i64, padding = dense<0> : tensor<4xi64>, strides = dense<2> : tensor<2xi64>} : (tensor<1x1x4x4x!FHE.eint<4>>, tensor<1x1x2x2xi5>, tensor<1xi5>) -> tensor<1x1x2x2x!FHE.eint<4>>
+  return %0 : tensor<1x1x2x2x!FHE.eint<4>>
+}

docs/howto/configure.md

@@ -70,9 +70,9 @@ Additional kwargs to `compile` functions take higher precedence. So if you set t
   * Error probability for individual table lookups. If set, all table lookups will have the probability of a non-exact result smaller than the set value. See [Exactness](../getting-started/exactness.md) to learn more.
 * **global\_p\_error**: Optional\[float] = None
   * Global error probability for the whole circuit. If set, the whole circuit will have the probability of a non-exact result smaller than the set value. See [Exactness](../getting-started/exactness.md) to learn more.
-* **single\_precision**: bool = True
+* **single\_precision**: bool = False
   * Use single precision for the whole circuit.
-* **parameter\_selection\_strategy**: (fhe.ParameterSelectionStrategy) = fhe.ParameterSelectionStrategy.MONO
+* **parameter\_selection\_strategy**: (fhe.ParameterSelectionStrategy) = fhe.ParameterSelectionStrategy.MULTI
   * Set how cryptographic parameters are selected.
 * **jit**: bool = False
   * Enable JIT compilation.

docs/tutorial/multi_parameters.md

@@ -1,11 +1,11 @@
 # Multi Parameters
 
-Integers in Concrete are encrypted and processed according to a set of cryptographic parameters. By default, only a single set of such parameters are selected by Concrete Optimizer. This is not the best approach for every use case so multi parameters are introduced.
+Integers in Concrete are encrypted and processed according to a set of cryptographic parameters. By default, multiple of such parameters are selected by Concrete Optimizer. This might not be the best approach for every use case and there is the option to use mono parameters.
 
-When they are enabled, a different set of parameters are selected for each bit-width in the circuit, which results in:
+When multi parameters are enabled, a different set of parameters are selected for each bit-width in the circuit, which results in:
 - Faster execution (generally).
 - Slower key generation.
 - Larger keys.
 - Larger memory usage during execution.
 
-To enable them, you can use `parameter_selection_strategy=fhe.ParameterSelectionStrategy.MULTI` configuration option.
+To disable it, you can use `parameter_selection_strategy=fhe.ParameterSelectionStrategy.MONO` configuration option.

docs/tutorial/multi_precision.md

@@ -70,8 +70,4 @@ return %4
 
 In this case, we kept `x` as 2-bits, but set the table lookup result and `y` to be 6-bits, so that the addition can be performed.
 
-This style of bit-width assignment is called multi-precision and it is currently disabled by default. To enable it, you can use the `single_precision=False` configuration option.
-
-{% hint style="info" %}
-Multi precision will become the default option in the near future.
-{% endhint %}
+This style of bit-width assignment is called multi-precision, and it is enabled by default. To disable it and use a single precision across the circuit, you can use the `single_precision=True` configuration option.

frontends/concrete-python/Makefile

@@ -30,14 +30,17 @@ pytest:
 	export LD_PRELOAD=$(RUNTIME_LIBRARY)
 	export PYTHONPATH=$(BINDINGS_DIRECTORY)
 
-	# test single precision
+	# test single precision, mono params
 	pytest tests -svv -n auto \
+		--precision=single \
+		--strategy=mono \
 		--key-cache "${KEY_CACHE_DIRECTORY}" \
 		-m "${PYTEST_MARKERS}"
 
-	# test multi precision
+	# test multi precision, multi params
 	pytest tests -svv -n auto \
 		--precision=multi \
+		--strategy=multi \
 		--cov=concrete \
 		--cov-fail-under=100 \
 		--cov-report=term-missing:skip-covered \

frontends/concrete-python/concrete/fhe/compilation/configuration.py

@@ -90,10 +90,10 @@ def __init__(
         p_error: Optional[float] = None,
         global_p_error: Optional[float] = None,
         auto_adjust_rounders: bool = False,
-        single_precision: bool = True,
+        single_precision: bool = False,
         parameter_selection_strategy: Union[
             ParameterSelectionStrategy, str
-        ] = ParameterSelectionStrategy.MONO,
+        ] = ParameterSelectionStrategy.MULTI,
         show_progress: bool = False,
         progress_title: str = "",
         progress_tag: Union[bool, int] = False,