[oneDNN] GRU BF16 kernel (#27731)

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -1894,7 +1894,8 @@ PDNode *patterns::QuantizePlacement::operator()(
 
 PDNode *patterns::Bfloat16Placement::operator()(
     const std::unordered_set<std::string> &bfloat16_enabled_op_types) {
-  std::unordered_set<std::string> supported_op_types{"conv2d"};
+  std::unordered_set<std::string> supported_op_types =
+      std::unordered_set<std::string>({"conv2d", "fusion_gru"});
   if (!bfloat16_enabled_op_types.empty()) {
     supported_op_types = bfloat16_enabled_op_types;
   }

paddle/fluid/operators/fused/mkldnn/fusion_gru_mkldnn_op.cc

@@ -86,7 +86,7 @@ class GRUMKLDNNHandler : public platform::MKLDNNHandlerT<T, dnnl::gru_forward> {
 
       // Weights for int8 kernel are of a type s8
       const auto weights_dt =
-          is_INT8 ? dnnl::memory::data_type::s8 : dnnl::memory::data_type::f32;
+          is_INT8 ? dnnl::memory::data_type::s8 : MKLDNNGetDataType<T>();
 
       // oneDNN RNN dimensions
       const int64_t D = 1;  // Directions
@@ -226,6 +226,8 @@ class GRUMKLDNNHandler : public platform::MKLDNNHandlerT<T, dnnl::gru_forward> {
   }
 
   // TODO(grygielski) H0 is for now persistable
+  // TODO(jczaja) H0 should be updated each iter and of T type (Fusion pass does
+  // not support in yet)
   std::shared_ptr<dnnl::memory> AcquireH0Memory(const Tensor* h0) {
     const std::string h0_key = memory_key_ + "@h0";
     auto memory_p =
@@ -397,14 +399,14 @@ template <typename T>
 class FusionGRUMKLDNNKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& ctx) const override {
-    const bool is_INT8 = std::is_same<T, uint8_t>::value;
+    const bool is_bf16 = std::is_same<T, paddle::platform::bfloat16>::value;
     const bool force_fp32_output = ctx.Attr<bool>("force_fp32_output");
 
-    // TODO(grygielski) Add option for bfloat
-    if (!is_INT8 || force_fp32_output) {
+    // BF16 does not support force output
+    if (!is_bf16 && force_fp32_output) {
       RunKernel<float>(ctx);
     } else {
-      RunKernel<uint8_t>(ctx);
+      RunKernel<T>(ctx);
     }
   }
 
@@ -495,4 +497,5 @@ class FusionGRUMKLDNNKernel : public framework::OpKernel<T> {
 namespace ops = paddle::operators;
 REGISTER_OP_KERNEL(fusion_gru, MKLDNN, paddle::platform::CPUPlace,
                    ops::FusionGRUMKLDNNKernel<float>,
+                   ops::FusionGRUMKLDNNKernel<paddle::platform::bfloat16>,
                    ops::FusionGRUMKLDNNKernel<uint8_t>);

python/paddle/fluid/tests/unittests/mkldnn/test_fusion_gru_bf16_mkldnn_op.py

+#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import unittest
+import numpy as np
+import struct
+import paddle.fluid.core as core
+from paddle.fluid.tests.unittests.op_test import OpTest, convert_float_to_uint16
+from paddle.fluid.tests.unittests.op_test import OpTest
+from paddle.fluid.tests.unittests.test_fusion_gru_op import fusion_gru
+from paddle.fluid.tests.unittests.test_fusion_lstm_op import fc, ACTIVATION
+
+
+@unittest.skipIf(not core.supports_bfloat16(),
+                 "place does not support BF16 evaluation")
+class TestFusionGRUBF16MKLDNNOp(OpTest):
+    def set_confs(self):
+        self.mkldnn_data_type = False
+
+    def setUp(self):
+        self.op_type = "fusion_gru"
+        self.lod = [[2, 4, 3]]
+        self.M = 3
+        self.D = 5
+        self.is_reverse = False
+        self.with_h0 = False
+        self.use_mkldnn = True
+        self._cpu_only = True
+        self.with_bias = True
+        self.act_state = 'tanh'
+        self.act_gate = 'sigmoid'
+        self.origin_mode = False
+        self.use_mkldnn = True
+        self.force_fp32_output = False
+        self.set_confs()
+
+        T = sum(self.lod[0])
+        N = len(self.lod[0])
+
+        # fp32 X input for reference implementation and
+        # corressponding bf16 data as input to GRU oneDNN bf16 kernel
+        x_fp32 = np.random.rand(T, self.M).astype('float32')
+        x_bf16 = convert_float_to_uint16(x_fp32)
+
+        wx_fp32 = np.random.rand(self.M, 3 * self.D).astype('float32')
+        wh_fp32 = np.random.rand(self.D, 3 * self.D).astype('float32')
+
+        # bias is fp32 despite other inputs being in bf16
+        bias = np.random.rand(
+            1, 3 * self.D).astype('float32') if self.with_bias else np.zeros(
+                (1, 3 * self.D), dtype='float32')
+
+        h0_fp32 = np.random.rand(
+            N, self.D).astype('float32') if self.with_h0 else np.zeros(
+                (N, self.D), dtype='float32')
+
+        _, _, _, hidden = fusion_gru(
+            x_fp32, self.lod, h0_fp32, wx_fp32, wh_fp32, bias, self.is_reverse,
+            self.origin_mode, ACTIVATION[self.act_state],
+            ACTIVATION[self.act_gate])
+
+        hidden_bf16 = convert_float_to_uint16(hidden)
+
+        self.inputs = {
+            'X': (x_bf16, self.lod),
+            'WeightX': wx_fp32,
+            'WeightH': wh_fp32
+        }
+
+        if self.with_bias:
+            self.inputs['Bias'] = bias
+
+        if self.with_h0:
+            self.inputs['H0'] = h0_bf16
+
+        h0_bf16 = convert_float_to_uint16(h0_fp32)
+        self.outputs = {'Hidden': (hidden_bf16, self.lod)}
+
+        self.attrs = {
+            'activation': self.act_state,
+            'gate_activation': self.act_gate,
+            'is_reverse': self.is_reverse,
+            'origin_mode': self.origin_mode,
+            'force_fp32_output': self.force_fp32_output,
+            'use_mkldnn': self.use_mkldnn
+        }
+
+
+class TestFusionGRUINT8MKLDNNOp2(TestFusionGRUBF16MKLDNNOp):
+    def set_confs(self):
+        self.origin_mode = False
+
+
+class TestFusionGRUINT8MKLDNNOp3(TestFusionGRUBF16MKLDNNOp):
+    def set_confs(self):
+        self.with_bias = False
+
+
+if __name__ == "__main__":
+    unittest.main()