Update to v0.22.0
- remove identityN and placeholder
- add div
- update serialization_lib hash
- update apply_scale_16() assertion
- regenerate examples/ due to serialization_lib change
Change-Id: I7183d92bec33697c65adfc07cb8eb89c6882675a
diff --git a/examples/test_add_1x4x4x4_f32/flatbuffer-tf/test_add_1x4x4x4_f32.tosa b/examples/test_add_1x4x4x4_f32/flatbuffer-tf/test_add_1x4x4x4_f32.tosa
index 7a195af..003d1bb 100644
--- a/examples/test_add_1x4x4x4_f32/flatbuffer-tf/test_add_1x4x4x4_f32.tosa
+++ b/examples/test_add_1x4x4x4_f32/flatbuffer-tf/test_add_1x4x4x4_f32.tosa
Binary files differ
diff --git a/examples/test_add_1x4x4x4_f32/flatbuffer-tflite/test_add_1x4x4x4_f32.tosa b/examples/test_add_1x4x4x4_f32/flatbuffer-tflite/test_add_1x4x4x4_f32.tosa
index c686131..864aaac 100644
--- a/examples/test_add_1x4x4x4_f32/flatbuffer-tflite/test_add_1x4x4x4_f32.tosa
+++ b/examples/test_add_1x4x4x4_f32/flatbuffer-tflite/test_add_1x4x4x4_f32.tosa
Binary files differ
diff --git a/examples/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11/flatbuffer-tf/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11.tosa b/examples/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11/flatbuffer-tf/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11.tosa
index 1fb5f17..ea794c8 100644
--- a/examples/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11/flatbuffer-tf/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11.tosa
+++ b/examples/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11/flatbuffer-tf/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11.tosa
Binary files differ
diff --git a/examples/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11/flatbuffer-tflite/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11.tosa b/examples/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11/flatbuffer-tflite/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11.tosa
index d1b740b..dfc7c9c 100644
--- a/examples/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11/flatbuffer-tflite/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11.tosa
+++ b/examples/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11/flatbuffer-tflite/test_conv2d_1x1_1x32x32x8_f32_st11_padSAME_dilat11.tosa
Binary files differ
diff --git a/examples/test_conv2d_1x1_1x32x32x8_qi8_st11_padSAME_dilat11/flatbuffer-tflite/test_conv2d_1x1_1x32x32x8_qi8_st11_padSAME_dilat11.tosa b/examples/test_conv2d_1x1_1x32x32x8_qi8_st11_padSAME_dilat11/flatbuffer-tflite/test_conv2d_1x1_1x32x32x8_qi8_st11_padSAME_dilat11.tosa
index 30bd194..1e21d49 100644
--- a/examples/test_conv2d_1x1_1x32x32x8_qi8_st11_padSAME_dilat11/flatbuffer-tflite/test_conv2d_1x1_1x32x32x8_qi8_st11_padSAME_dilat11.tosa
+++ b/examples/test_conv2d_1x1_1x32x32x8_qi8_st11_padSAME_dilat11/flatbuffer-tflite/test_conv2d_1x1_1x32x32x8_qi8_st11_padSAME_dilat11.tosa
Binary files differ
diff --git a/reference_model/src/ops/control_flow.cc b/reference_model/src/ops/control_flow.cc
index 827e01f..1a6a63a 100644
--- a/reference_model/src/ops/control_flow.cc
+++ b/reference_model/src/ops/control_flow.cc
@@ -93,6 +93,8 @@
return 1;
}
+ tensor->setIsValid();
+
// Push ready consumers to the next node list
for (auto gn : tensor->getConsumers())
{
@@ -292,8 +294,7 @@
int OpWhileLoop::eval()
{
- TosaReference::Tensor0<bool> cond_output_ctensor(std::string("cond_output"), DType_BOOL,
- std::vector<int32_t>({}));
+ TosaReference::Tensor0<bool> cond_output_ctensor(std::string("cond_output"), DType_BOOL, std::vector<int32_t>({}));
cond_output_ctensor.allocate();
std::vector<TosaReference::Tensor*> cond_block_outputs;
diff --git a/reference_model/src/ops/data_nodes.cc b/reference_model/src/ops/data_nodes.cc
index 883cd1b..baae019 100644
--- a/reference_model/src/ops/data_nodes.cc
+++ b/reference_model/src/ops/data_nodes.cc
@@ -42,29 +42,6 @@
return GraphNode::eval();
}
-OpPlaceholder::OpPlaceholder(uint64_t id_)
- : GraphNode(Op_PLACEHOLDER, id_)
-{
- setRequiredOperands(0, 1);
-}
-
-OpPlaceholder::~OpPlaceholder()
-{}
-
-int OpPlaceholder::checkTensorAttributes()
-{
- if (validateRequiredOperands())
- return 1;
-
- return 0;
-}
-
-int OpPlaceholder::eval()
-{
- // Evaluation is trivial for placeholders
- return GraphNode::eval();
-}
-
template <int Rank, DType Dtype>
OpIdentity<Rank, Dtype>::OpIdentity(TosaAttributeBase* attribute_, TosaQuantInfoBase* qinfo_, uint64_t id_)
: GraphNode(Op_IDENTITY, id_)
@@ -107,64 +84,11 @@
return GraphNode::eval();
}
-template <int Rank, DType Dtype>
-OpIdentityN<Rank, Dtype>::OpIdentityN(TosaAttributeBase* attribute_, TosaQuantInfoBase* qinfo_, uint64_t id_)
- : GraphNode(Op_IDENTITYN, id_)
-{
- setRequiredRank(0, 6);
-}
-
-template <int Rank, DType Dtype>
-OpIdentityN<Rank, Dtype>::~OpIdentityN()
-{}
-
-template <int Rank, DType Dtype>
-int OpIdentityN<Rank, Dtype>::checkTensorAttributes()
-{
-
- if (inputs.size() != outputs.size())
- {
- printNodeValidationError("Input and output tensor list lengths are not equal");
- return 1;
- }
-
- for (size_t i = 0; i < inputs.size(); i++)
- {
- ins.push_back(dynamic_cast<TosaReference::TensorTemplate<TIn>*>(inputs[i]));
- outs.push_back(dynamic_cast<TosaReference::TensorTemplate<TOut>*>(outputs[i]));
-
- if (ins[i]->matchRankTypeShape(*outs[i]))
- {
- printNodeValidationError("Input and output tensor rank, type, or shape do not match");
- return 1;
- }
- }
-
- return 0;
-}
-
-template <int Rank, DType Dtype>
-int OpIdentityN<Rank, Dtype>::eval()
-{
- for (size_t i = 0; i < ins.size(); i++)
- {
- outs[i]->getTensor() = ins[i]->getTensor();
- }
-
- return GraphNode::eval();
-}
-
// template explicit instantiation
-// note OpConst and OpPlaceholder are not templated
+// note OpConst is not templated
DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentity, FLOAT);
DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentity, INT8);
DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentity, INT16);
DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentity, INT32);
DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentity, BOOL);
-
-DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentityN, FLOAT);
-DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentityN, INT8);
-DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentityN, INT16);
-DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentityN, INT32);
-DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentityN, BOOL);
diff --git a/reference_model/src/ops/data_nodes.h b/reference_model/src/ops/data_nodes.h
index bec4669..a02d441 100644
--- a/reference_model/src/ops/data_nodes.h
+++ b/reference_model/src/ops/data_nodes.h
@@ -31,16 +31,6 @@
virtual int eval();
};
-class OpPlaceholder : public GraphNode
-{
-public:
- OpPlaceholder(uint64_t id_);
- virtual ~OpPlaceholder();
-
- virtual int checkTensorAttributes();
- virtual int eval();
-};
-
template <int Rank, DType Dtype>
class OpIdentity : public GraphNode
{
@@ -61,26 +51,6 @@
TosaReference::TensorTemplate<TOut>* out;
};
-template <int Rank, DType Dtype>
-class OpIdentityN : public GraphNode
-{
-public:
- OpIdentityN(TosaAttributeBase* attribute_, TosaQuantInfoBase* qinfo_, uint64_t id_);
- virtual ~OpIdentityN();
-
- virtual int checkTensorAttributes();
- virtual int eval();
-
- using InEigenType = typename GetEigenType<Dtype>::type;
- using OutEigenType = typename GetEigenType<Dtype>::type;
- using TIn = Eigen::Tensor<InEigenType, Rank>;
- using TOut = Eigen::Tensor<OutEigenType, Rank>;
-
-protected:
- std::vector<TosaReference::TensorTemplate<TIn>*> ins;
- std::vector<TosaReference::TensorTemplate<TOut>*> outs;
-};
-
}; // namespace TosaReference
#endif
diff --git a/reference_model/src/ops/ewise_binary.cc b/reference_model/src/ops/ewise_binary.cc
index fc587f1..76cebeb 100644
--- a/reference_model/src/ops/ewise_binary.cc
+++ b/reference_model/src/ops/ewise_binary.cc
@@ -298,6 +298,27 @@
}
template <int Rank, DType Dtype>
+int OpDiv<Rank, Dtype>::register_fcn()
+{
+ switch (InDtype)
+ {
+ case DType_INT32:
+ this->fcn = [this](InEigenType a, InEigenType b) -> OutEigenType {
+ ASSERT_MSG_NODE(b != 0, "OpDiv: divisor must be non-zero value");
+ int64_t res_in_64 = static_cast<int64_t>(a) / b;
+ int64_t i32_max_in_64 = static_cast<int64_t>(std::numeric_limits<InEigenType>::max());
+ ASSERT_MSG_NODE(a <= i32_max_in_64, "OpDiv: result not in i32 range");
+ return static_cast<InEigenType>(res_in_64);
+ };
+ break;
+ default:
+ FATAL_ERROR_NODE("unsupported DType %s", EnumNamesDType()[InDtype]);
+ }
+
+ return 0;
+}
+
+template <int Rank, DType Dtype>
int OpLogicalAnd<Rank, Dtype>::register_fcn()
{
switch (Dtype)
@@ -579,6 +600,8 @@
DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpBitwiseXor, INT16);
DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpBitwiseXor, INT32);
+DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpDiv, INT32);
+
DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpLogicalAnd, BOOL);
DEF_INSTANTIATE_RANK0_6_ONE_RANK_ONE_TYPE(OpLogicalLeftShift, INT8);
diff --git a/reference_model/src/ops/ewise_binary.h b/reference_model/src/ops/ewise_binary.h
index 5bc5630..6b9c98d 100644
--- a/reference_model/src/ops/ewise_binary.h
+++ b/reference_model/src/ops/ewise_binary.h
@@ -125,6 +125,7 @@
DEF_TEMPLATE_BINARY_OP_DEFAULT(BitwiseAnd, BITWISE_AND)
DEF_TEMPLATE_BINARY_OP_DEFAULT(BitwiseOr, BITWISE_OR)
DEF_TEMPLATE_BINARY_OP_DEFAULT(BitwiseXor, BITWISE_XOR)
+DEF_TEMPLATE_BINARY_OP_DEFAULT(Div, DIV)
DEF_TEMPLATE_BINARY_OP_DEFAULT(LogicalAnd, LOGICAL_AND)
DEF_TEMPLATE_BINARY_OP_DEFAULT(LogicalLeftShift, LOGICAL_LEFT_SHIFT)
DEF_TEMPLATE_BINARY_OP_DEFAULT(LogicalRightShift, LOGICAL_RIGHT_SHIFT)
diff --git a/reference_model/src/ops/op_factory.cc b/reference_model/src/ops/op_factory.cc
index b326c63..440d624 100644
--- a/reference_model/src/ops/op_factory.cc
+++ b/reference_model/src/ops/op_factory.cc
@@ -134,6 +134,9 @@
DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpBitwiseXor, INT16);
DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpBitwiseXor, INT32);
break;
+ case Op_DIV:
+ DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpDiv, INT32);
+ break;
case Op_LOGICAL_AND:
DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpLogicalAnd, BOOL);
break;
@@ -346,8 +349,6 @@
// data_nodes
case Op_CONST:
return new OpConst(id);
- case Op_PLACEHOLDER:
- return new OpPlaceholder(id);
case Op_IDENTITY:
DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentity, FLOAT);
DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentity, INT32);
@@ -355,13 +356,6 @@
DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentity, INT16);
DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentity, BOOL);
break;
- case Op_IDENTITYN:
- DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentityN, FLOAT);
- DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentityN, INT32);
- DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentityN, INT8);
- DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentityN, INT16);
- DEF_FACTORY_RANK0_6_ONE_RANK_ONE_TYPE(OpIdentityN, BOOL);
- break;
// type_conversion
case Op_CAST:
diff --git a/reference_model/src/quant_util.h b/reference_model/src/quant_util.h
index f07dd10..c595869 100644
--- a/reference_model/src/quant_util.h
+++ b/reference_model/src/quant_util.h
@@ -65,8 +65,8 @@
static int32_t apply_scale_16(int64_t value, int16_t multiplier, int32_t shift)
{
ASSERT_MSG(multiplier >= 0, "apply_scale_16() error: multiplier should >= 0 but is %d", multiplier);
- ASSERT_MSG(value >= -(static_cast<int64_t>(1) << 47) && value < (static_cast<int64_t>(1) << 47),
- "apply_scale_16() error: value should be within [-(1^47), 1^47]");
+ ASSERT_MSG(shift >= 2 && shift <= 62, "apply_scale_16() error: shift should be within [2, 62] but is %d",
+ shift);
int64_t round = 1L << (shift - 1);
int64_t result = value * (int64_t)multiplier + round;
result = result >> shift;
diff --git a/reference_model/src/subgraph_traverser.cc b/reference_model/src/subgraph_traverser.cc
index 5096ffa..1995b5c 100644
--- a/reference_model/src/subgraph_traverser.cc
+++ b/reference_model/src/subgraph_traverser.cc
@@ -499,7 +499,6 @@
// For each node, read this list, link up the tensors with their inputs/outputs
for (GraphNode* currNode : nodes)
{
-
// Link inputs/consuming nodes
for (std::string& name : currNode->getInputNames())
{
@@ -566,36 +565,18 @@
for (TosaReference::Tensor* currTensor : tensors)
{
- if (!currTensor->getProducer() && currTensor->getConsumers().empty())
+ // It's okay for block input tensor not being consumed by operators.
+ // This is common in control flow op execution.
+ if (!currTensor->getIsSubgraphInput())
{
- WARNING("Graph inconsistency: TosaReference::Tensor %s has no producers or consumers\n",
- currTensor->getName().c_str());
- return 1;
- }
-
- if (currTensor->getIsSubgraphInput())
- {
- if (currTensor->getProducer() && currTensor->getProducer()->getOp() != Op_PLACEHOLDER)
+ if (!currTensor->getProducer() && currTensor->getConsumers().empty())
{
- WARNING("Graph inconsistency: TosaReference::Tensor %s is a subgraph input and has a producer\n",
+ WARNING("Graph inconsistency: TosaReference::Tensor %s has no producers or consumers\n",
currTensor->getName().c_str());
return 1;
}
}
- // comment this check out as this is possible when graph have multiple output
- // for example:
- // %0 = add(%arg0, %arg1)
- // %1 = mul(%arg0, %0)
- // yields(%0, %1)
- //if (currTensor->getIsSubgraphOutput()) {
- // if (!currTensor->getConsumers().empty()) {
- // WARNING ("Graph inconsistency: TosaReference::Tensor %s is a subgraph output and has a consumer\n",
- // currTensor->getName().c_str());
- // return 1;
- // }
- //}
-
if (g_func_config.tosa_profile == 0)
{
DType dtype = currTensor->getDtype();
diff --git a/thirdparty/serialization_lib b/thirdparty/serialization_lib
index 2364dcd..a8b4eaf 160000
--- a/thirdparty/serialization_lib
+++ b/thirdparty/serialization_lib
@@ -1 +1 @@
-Subproject commit 2364dcd7241d730021bf68e000e5a6411b9f09d1
+Subproject commit a8b4eafda31fe41b99a46c09c131ac7295382570
diff --git a/verif/tosa_serializer.py b/verif/tosa_serializer.py
index 726ffc4..5ed9877 100644
--- a/verif/tosa_serializer.py
+++ b/verif/tosa_serializer.py
@@ -548,8 +548,6 @@
tens = self.currBasicBlock.addTensor(name, shape, dtype, None, filename)
# This is always an input to the block
self.currBasicBlock.addInput(name)
- # Add the operator now
- self.currBasicBlock.addOperator(tosa.Op.Op().PLACEHOLDER, [], name)
if vals is not None:
np.save(os.path.join(self.pathPrefix, filename), vals, False)
@@ -586,7 +584,6 @@
return tens
def addInputTensor(self, tensor):
- self.currBasicBlock.addOperator(tosa.Op.Op().PLACEHOLDER, [], tensor.name)
self.currBasicBlock.addTensor(tensor.name, tensor.shape, tensor.dtype)
self.currBasicBlock.addInput(tensor.name)
@@ -606,10 +603,8 @@
def addOperator(self, op, inputs, outputs, attributes=None, quant_info=None):
- if op == tosa.Op.Op().PLACEHOLDER or op == tosa.Op.Op().CONST:
- raise Exception(
- "Use addPlaceholderTensor() or addConstTensor() to add PLACEHOLDER and CONST ops"
- )
+ if op == tosa.Op.Op().CONST:
+ raise Exception("Use addConstTensor() to add CONST ops")
return self.currBasicBlock.addOperator(
op, inputs, outputs, attributes, quant_info
diff --git a/verif/tosa_test_gen.py b/verif/tosa_test_gen.py
index 7731a75..bc97f15 100644
--- a/verif/tosa_test_gen.py
+++ b/verif/tosa_test_gen.py
@@ -1710,10 +1710,101 @@
else:
raise Exception("OpArithmeticRightShift: invalid input dtype")
else:
- arr = self.getRandTensor(shapeList[0], dtypeList[idx])
+ arr = self.getRandTensor(shape, dtypeList[idx])
placeholders.append(self.ser.addPlaceholder(shape, dtypeList[idx], arr))
tens.extend(placeholders)
+ elif op["op"] == Op.DIV:
+ assert (
+ pCount == 2 and cCount == 0
+ ), "Op.Div must have 2 placeholders, 0 consts"
+
+ placeholders = []
+
+ # Two invalid cases for Op.DIV:
+ # 1. divisor == 0
+ # 2. dividend == (1<<31) and divisor == -1
+ while True:
+ dividend_arr = self.getRandTensor(shapeList[0], dtypeList[0])
+ divisor_arr = self.getRandTensor(shapeList[1], dtypeList[1])
+
+ if (divisor_arr == 0).any():
+ continue
+
+ if (dividend_arr == (2 ** 31)).any() and (divisor_arr == -1).any():
+ continue
+
+ break
+
+ placeholders.append(
+ self.ser.addPlaceholder(shapeList[0], dtypeList[0], dividend_arr)
+ )
+ placeholders.append(
+ self.ser.addPlaceholder(shapeList[1], dtypeList[1], divisor_arr)
+ )
+
+ tens.extend(placeholders)
+ elif op["op"] == Op.MUL:
+ assert (
+ pCount == 2 and cCount == 0
+ ), "Op.MUL must have 2 placeholders, 0 consts"
+
+ if dtypeList[0] == DType.FLOAT:
+ tens.extend(self.buildPlaceholderTensors(shapeList[:], dtypeList[:]))
+ else:
+ placeholders = []
+
+ # Make sure multiply result in int32 range
+ shift = testArgs[0]
+ if dtypeList[0] == DType.INT8:
+ num_bits = 8
+ elif dtypeList[0] == DType.INT16:
+ num_bits = 16
+ elif dtypeList[0] == DType.INT32:
+ num_bits = 32
+ else:
+ raise Exception("OpMul: invalid input dtype")
+
+ for idx, shape in enumerate(shapeList[:]):
+ low = -(2 ** (num_bits - 1))
+ high = (2 ** (num_bits - 1)) - 1
+
+ a_arr = np.int32(
+ self.rng.integers(low=low, high=high, size=shapeList[0])
+ )
+ b_arr = np.int32(
+ self.rng.integers(low=low, high=high, size=shapeList[1])
+ )
+
+ i = 0
+ while True:
+
+ a_arr_64 = a_arr.astype(np.int64)
+ b_arr_64 = b_arr.astype(np.int64)
+
+ if shift > 0:
+ rounding = 1 << (shift - 1)
+ result_arr = ((a_arr_64 * b_arr_64) + rounding) >> shift
+ else:
+ result_arr = a_arr_64 * b_arr_64
+
+ if (result_arr > -(2 ** 31)).all() and (
+ result_arr <= ((2 ** 31) - 1)
+ ).all():
+ break
+
+ i = i + 1
+ a_arr = a_arr // 2
+ b_arr = b_arr // 2
+
+ placeholders.append(
+ self.ser.addPlaceholder(shapeList[0], dtypeList[0], a_arr)
+ )
+ placeholders.append(
+ self.ser.addPlaceholder(shapeList[1], dtypeList[1], b_arr)
+ )
+
+ tens.extend(placeholders)
else:
tens.extend(
self.buildPlaceholderTensors(shapeList[0:pCount], dtypeList[0:pCount])
@@ -1858,7 +1949,6 @@
"build_fcn": (build_argmax, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_NARROW_INT_FP,
},
-
"avg_pool2d": {
"op": Op.AVG_POOL2D,
"operands": (1, 0),
@@ -1867,7 +1957,6 @@
"qgen": TosaQuantGen.qgUnary,
"types": TYPE_NARROW_INT_FP,
},
-
# Templated operator. Filled in by createDynamicOpLists
"conv2d_TEMPLATE": {
"op": Op.CONV2D,
@@ -1878,9 +1967,7 @@
"types": TYPE_CONV2D,
"template": True,
},
-
# Conv3d TBD
-
# Templated operator. Filled in by createDynamicOpLists
"depthwise_conv2d_TEMPLATE": {
"op": Op.DEPTHWISE_CONV2D,
@@ -1896,7 +1983,6 @@
"types": TYPE_CONV2D,
"template": True,
},
-
"fully_connected": {
"op": Op.FULLY_CONNECTED,
"operands": (1, 2),
@@ -1905,7 +1991,6 @@
"qgen": TosaQuantGen.qgConv,
"types": TYPE_CONV2D,
},
-
"matmul": {
"op": Op.MATMUL,
"operands": (2, 0),
@@ -1914,7 +1999,6 @@
"qgen": TosaQuantGen.qgMatmul,
"types": TYPE_NARROW_INT_FP,
},
-
"max_pool2d": {
"op": Op.MAX_POOL2D,
"operands": (1, 0),
@@ -1922,7 +2006,6 @@
"build_fcn": (build_pool2d, TosaTensorGen.tgNHWC, TosaArgGen.agPooling),
"types": TYPE_NARROW_INT_FP,
},
-
# Templated operator. Filled in by createDynamicOpLists
"transpose_conv2d_TEMPLATE": {
"op": Op.TRANSPOSE_CONV2D,
@@ -1937,7 +2020,6 @@
"types": TYPE_CONV2D,
"template": True,
},
-
# Activation functions
"clamp": {
"op": Op.CLAMP,
@@ -1945,28 +2027,24 @@
"build_fcn": (build_clamp, TosaTensorGen.tgBasic, None),
"types": TYPE_NARROW_INT_FP,
},
-
"relun": {
"op": Op.RELUN,
"operands": (1, 0),
"build_fcn": (build_relun, TosaTensorGen.tgBasic, None),
"types": TYPE_FI32,
},
-
"sigmoid": {
"op": Op.SIGMOID,
"operands": (1, 0),
"build_fcn": (build_sigmoid, TosaTensorGen.tgBasic, None),
"types": TYPE_FP,
},
-
"tanh": {
"op": Op.TANH,
"operands": (1, 0),
"build_fcn": (build_tanh, TosaTensorGen.tgBasic, None),
"types": TYPE_FP,
},
-
# Elementwise Binary Operators
"add": {
"op": Op.ADD,
@@ -1974,7 +2052,6 @@
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_FI32,
},
-
"arithmetic_right_shift": {
"op": Op.ARITHMETIC_RIGHT_SHIFT,
"operands": (2, 0),
@@ -1985,98 +2062,90 @@
),
"types": TYPE_INT,
},
-
"bitwise_and": {
"op": Op.BITWISE_AND,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_INT,
},
-
"bitwise_or": {
"op": Op.BITWISE_OR,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_INT,
},
-
"bitwise_xor": {
"op": Op.BITWISE_XOR,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_INT,
},
-
+ "div": {
+ "op": Op.DIV,
+ "operands": (2, 0),
+ "build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
+ "types": [DType.INT32],
+ },
"logical_and": {
"op": Op.LOGICAL_AND,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_BOOL,
},
-
"logical_left_shift": {
"op": Op.LOGICAL_LEFT_SHIFT,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_INT,
},
-
"logical_right_shift": {
"op": Op.LOGICAL_RIGHT_SHIFT,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_INT,
},
-
"logical_or": {
"op": Op.LOGICAL_OR,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_BOOL,
},
-
"logical_xor": {
"op": Op.LOGICAL_XOR,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_BOOL,
},
-
"maximum": {
"op": Op.MAXIMUM,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_FI32,
},
-
"minimum": {
"op": Op.MINIMUM,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_FI32,
},
-
"mul": {
"op": Op.MUL,
"operands": (2, 0),
"build_fcn": (build_mul, TosaTensorGen.tgBroadcastFuzz, TosaArgGen.agMul),
"types": TYPE_INT_FP,
},
-
"pow": {
"op": Op.POW,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBasic, None),
"types": TYPE_FP,
},
-
"sub": {
"op": Op.SUB,
"operands": (2, 0),
"build_fcn": (build_binary_broadcast, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_FI32,
},
-
"table": {
"op": Op.TABLE,
# Use the automatic generation functions to create the input array
@@ -2086,7 +2155,6 @@
"build_fcn": (build_table, TosaTensorGen.tgBasic, None),
"types": [DType.INT16],
},
-
# Elementwise Unary operators
"abs": {
"op": Op.ABS,
@@ -2094,56 +2162,48 @@
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": TYPE_FI32,
},
-
"bitwise_not": {
"op": Op.BITWISE_NOT,
"operands": (1, 0),
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": TYPE_INT,
},
-
"ceil": {
"op": Op.CEIL,
"operands": (1, 0),
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": TYPE_FP,
},
-
"clz": {
"op": Op.CLZ,
"operands": (1, 0),
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": [DType.INT32],
},
-
"exp": {
"op": Op.EXP,
"operands": (1, 0),
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": TYPE_FP,
},
-
"floor": {
"op": Op.FLOOR,
"operands": (1, 0),
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": TYPE_FP,
},
-
"log": {
"op": Op.LOG,
"operands": (1, 0),
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": TYPE_FP,
},
-
"logical_not": {
"op": Op.LOGICAL_NOT,
"operands": (1, 0),
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": TYPE_BOOL,
},
-
"negate": {
"op": Op.NEGATE,
"operands": (1, 0),
@@ -2151,21 +2211,18 @@
"qgen": TosaQuantGen.qgUnary,
"types": TYPE_INT_FP,
},
-
"reciprocal": {
"op": Op.RECIPROCAL,
"operands": (1, 0),
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": TYPE_FP,
},
-
"rsqrt": {
"op": Op.RSQRT,
"operands": (1, 0),
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": TYPE_FP,
},
-
# Elementwise Ternary operators
"select": {
"op": Op.SELECT,
@@ -2173,7 +2230,6 @@
"build_fcn": (build_select, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_FIB,
},
-
# Comparison operators
"equal": {
"op": Op.EQUAL,
@@ -2181,21 +2237,18 @@
"build_fcn": (build_comparison, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_FI32,
},
-
"greater_equal": {
"op": Op.GREATER_EQUAL,
"operands": (2, 0),
"build_fcn": (build_comparison, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_FI32,
},
-
"greater": {
"op": Op.GREATER,
"operands": (2, 0),
"build_fcn": (build_comparison, TosaTensorGen.tgBroadcastFuzz, None),
"types": TYPE_FI32,
},
-
# Reduction operators
"reduce_all": {
"op": Op.REDUCE_ALL,
@@ -2203,42 +2256,36 @@
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_BOOL,
},
-
"reduce_any": {
"op": Op.REDUCE_ANY,
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_BOOL,
},
-
"reduce_max": {
"op": Op.REDUCE_MAX,
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_INT_FP,
},
-
"reduce_min": {
"op": Op.REDUCE_MAX,
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_INT_FP,
},
-
"reduce_product": {
"op": Op.REDUCE_PRODUCT,
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_FP,
},
-
"reduce_sum": {
"op": Op.REDUCE_SUM,
"operands": (1, 0),
"build_fcn": (build_reduce, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_FI32,
},
-
# Data layout operators
"concat": {
"op": Op.CONCAT,
@@ -2246,7 +2293,6 @@
"build_fcn": (build_concat, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_FIB,
},
-
"pad": {
"op": Op.PAD,
"operands": (1, 0),
@@ -2254,35 +2300,30 @@
"qgen": TosaQuantGen.qgPad,
"types": TYPE_FIB,
},
-
"reshape": {
"op": Op.RESHAPE,
"operands": (1, 0),
"build_fcn": (build_reshape, TosaTensorGen.tgBasic, TosaArgGen.agReshape),
"types": TYPE_FIB,
},
-
"reverse": {
"op": Op.REVERSE,
"operands": (1, 0),
"build_fcn": (build_reverse, TosaTensorGen.tgBasic, TosaArgGen.agAxis),
"types": TYPE_FIB,
},
-
"slice": {
"op": Op.SLICE,
"operands": (1, 0),
"build_fcn": (build_slice, TosaTensorGen.tgBasic, TosaArgGen.agSlice),
"types": TYPE_FIB,
},
-
"tile": {
"op": Op.TILE,
"operands": (1, 0),
"build_fcn": (build_tile, TosaTensorGen.tgBasic, TosaArgGen.agTile),
"types": TYPE_FIB,
},
-
"transpose": {
"op": Op.TRANSPOSE,
"operands": (1, 0),
@@ -2294,7 +2335,6 @@
),
"types": TYPE_FIB,
},
-
# Data nodes
"const": {
"op": Op.CONST,
@@ -2302,28 +2342,12 @@
"build_fcn": (build_placeholder, TosaTensorGen.tgBasic, None),
"types": TYPE_FIB,
},
-
"identity": {
"op": Op.IDENTITY,
"operands": (1, 0),
"build_fcn": (build_unary, TosaTensorGen.tgBasic, None),
"types": TYPE_FIB,
},
-
- "identityn": {
- "op": Op.IDENTITYN,
- "operands": (2, 0),
- "build_fcn": (build_identityn, TosaTensorGen.tgBasic, None),
- "types": TYPE_FIB,
- },
-
- "placeholder": {
- "op": Op.PLACEHOLDER,
- "operands": (1, 0),
- "build_fcn": (build_placeholder, TosaTensorGen.tgBasic, None),
- "types": TYPE_FIB,
- },
-
# Scatter/Gather
"gather": {
"op": Op.GATHER,
@@ -2333,7 +2357,6 @@
"build_fcn": (build_gather, TosaTensorGen.tgBasic, None),
"types": TYPE_INT_FP,
},
-
"scatter": {
"op": Op.SCATTER,
# Only specify 'values_in' tensor here.
@@ -2343,7 +2366,6 @@
"build_fcn": (build_scatter, TosaTensorGen.tgScatter, None),
"types": TYPE_INT_FP,
},
-
# Image operations
"resize": {
"op": Op.RESIZE,
@@ -2352,7 +2374,6 @@
"build_fcn": (build_resize, TosaTensorGen.tgNHWC, TosaArgGen.agResize),
"types": [DType.INT8, DType.INT16, DType.FLOAT],
},
-
# Type conversion
"cast": {
"op": Op.CAST,
@@ -2360,18 +2381,14 @@
"build_fcn": (build_cast, TosaTensorGen.tgBasic, TosaArgGen.agCast),
"types": [DType.FLOAT, DType.INT8, DType.INT16, DType.INT32, DType.BOOL],
},
-
"rescale": {
"op": Op.RESCALE,
"operands": (1, 0),
"build_fcn": (build_rescale, TosaTensorGen.tgBasic, TosaArgGen.agRescale),
"types": [DType.INT8, DType.INT16, DType.INT32, DType.INT48],
},
-
# Custom
# Not implemented.
-
-
# Control flow operators
# Two varients of cond_if, one that generates one of two constant tensors (no
# inputs to the basic blocks, one output) and another that either adds or subtracts two tensors