[IE CLDNN] Restrict bsv16_fsv16 convolution to int8 for batch 16 (#1954)

diff --git a/inference-engine/thirdparty/clDNN/src/layout_optimizer.cpp b/inference-engine/thirdparty/clDNN/src/layout_optimizer.cpp
index a44e076..bac02a2 100644 (file)
--- a/inference-engine/thirdparty/clDNN/src/layout_optimizer.cpp
+++ b/inference-engine/thirdparty/clDNN/src/layout_optimizer.cpp
@@ -481,19 +481,21 @@ bool layout_optimizer::convolution_bs_fs_yx_bsv16_fsv16_opt(const layout &input_
                                                             const layout& weights_layout,
                                                             std::shared_ptr<const convolution> conv) {
     // A set of rules that define when bs_fs_yx_bsv16_fsv16 mem format can be used
-    bool correct_batch = input_layout.size.batch[0] >= 16;
+    bool correct_batch = input_layout.size.batch[0] > 16;
     bool correct_feature = (input_layout.size.feature[0] % 16 == 0 || input_layout.size.feature[0] == 3) && conv->output_size.feature[0] % 16 == 0;
     bool fp16_ver = input_layout.data_type == data_types::f16 && input_layout.size.batch[0] % 32 == 0;
     bool fp32_ver = input_layout.data_type == data_types::f32 && input_layout.size.batch[0] % 16 == 0;
     bool single_group = conv->groups == 1;
-    bool int8_sup = (input_layout.data_type == data_types::i8 || input_layout.data_type == data_types::u8) &&
-                    input_layout.size.batch[0] % 16 == 0 && weights_layout.data_type == data_types::i8 &&
-                    (conv->activations_zero_points.empty() && conv->weights_zero_points.empty());
+
+    bool int8_sup = (input_layout.data_type == data_types::i8 || input_layout.data_type == data_types::u8);
+    if (int8_sup)
+        correct_batch = input_layout.size.batch[0] >= 16;
+    int8_sup &= (input_layout.size.batch[0] % 16 == 0 && weights_layout.data_type == data_types::i8 &&
+                 conv->activations_zero_points.empty() && conv->weights_zero_points.empty());
     auto ks_x = weights_layout.size.spatial[0];
     auto ks_y = weights_layout.size.spatial[1];
     int8_sup &= (input_layout.size.spatial[2] == 1 && ((ks_x == 1 && ks_y == 1) || (ks_x == 3 && ks_y == 3) || (ks_x == 7 && ks_y == 7)) &&
-                 input_layout.size.batch[0] % 16 == 0 && weights_layout.size.batch[0] % 32 == 0 && conv->groups == 1 &&
-                 conv->split() == 1 && conv->dilation == tensor{1});
+                 weights_layout.size.batch[0] % 32 == 0 && conv->split() == 1 && conv->dilation == tensor{1});
 
     return (int8_sup || fp16_ver || fp32_ver) && correct_feature && correct_batch && single_group;
 }