NFC:
Update const-fold tests to use regex which is the suggested way for matching. PiperOrigin-RevId: 312202071 Change-Id: I901de7936dc260eb968a835be826dfbd39b78c9f
This commit is contained in:
Karim Nosir
TensorFlower Gardener
parent
63926472df
commit
44c387f297
@ -8,13 +8,13 @@ func @add_float() -> (tensor<f32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>,
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%2 = constant dense< 3.5> : tensor<4xf32>
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%3 = constant dense<-0.5> : tensor<4xf32>
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// CHECK: %cst = constant dense<3.500000e+00> : tensor<4xf32>
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// CHECK: %cst_0 = constant dense<-5.000000e-01> : tensor<4xf32>
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// CHECK: %cst_1 = constant dense<6.000000e+00> : tensor<f32>
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// CHECK: %cst_2 = constant dense<4.000000e+00> : tensor<4xf32>
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// CHECK: %cst_3 = constant dense<5.000000e+00> : tensor<4xf32>
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// CHECK: %cst_4 = constant dense<3.000000e+00> : tensor<4xf32>
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// CHECK: %0 = tfl.add %cst, %cst_0 {fused_activation_function = "SIGN_BIT"} : tensor<4xf32>
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// CHECK: %[[CST:.*]] = constant dense<3.500000e+00> : tensor<4xf32>
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// CHECK: %[[CST_0:.*]] = constant dense<-5.000000e-01> : tensor<4xf32>
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// CHECK: %[[CST_1:.*]] = constant dense<6.000000e+00> : tensor<f32>
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// CHECK: %[[CST_2:.*]] = constant dense<4.000000e+00> : tensor<4xf32>
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// CHECK: %[[CST_3:.*]] = constant dense<5.000000e+00> : tensor<4xf32>
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// CHECK: %[[CST_4:.*]] = constant dense<3.000000e+00> : tensor<4xf32>
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// CHECK: %0 = tfl.add %[[CST]], %[[CST_0]] {fused_activation_function = "SIGN_BIT"} : tensor<4xf32>
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%5 = "tfl.add"(%0, %1) {fused_activation_function = "NONE"} : (tensor< f32>, tensor< f32>) -> tensor< f32>
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%6 = "tfl.add"(%0, %3) {fused_activation_function = "NONE"} : (tensor< f32>, tensor<4xf32>) -> tensor<4xf32>
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@ -33,10 +33,10 @@ func @add_int() -> (tensor<i32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>) {
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%2 = constant dense< 4> : tensor<4xi32>
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%3 = constant dense<-2> : tensor<4xi32>
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// CHECK: %cst = constant dense<9> : tensor<i32>
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// CHECK: %cst_0 = constant dense<6> : tensor<4xi32>
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// CHECK: %cst_1 = constant dense<5> : tensor<4xi32>
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// CHECK: %cst_2 = constant dense<2> : tensor<4xi32>
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// CHECK: %[[CST:.*]] = constant dense<9> : tensor<i32>
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// CHECK: %[[CST_0:.*]] = constant dense<6> : tensor<4xi32>
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// CHECK: %[[CST_1:.*]] = constant dense<5> : tensor<4xi32>
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// CHECK: %[[CST_2:.*]] = constant dense<2> : tensor<4xi32>
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%5 = "tfl.add"(%0, %1) {fused_activation_function = "NONE"} : (tensor< i32>, tensor< i32>) -> tensor< i32>
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%6 = "tfl.add"(%0, %3) {fused_activation_function = "NONE"} : (tensor< i32>, tensor<4xi32>) -> tensor<4xi32>
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@ -54,10 +54,10 @@ func @sub_float() -> (tensor<f32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>)
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%2 = constant dense< 3.5> : tensor<4xf32>
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%3 = constant dense<-0.5> : tensor<4xf32>
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// CHECK: %cst = constant dense<3.000000e+00> : tensor<f32>
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// CHECK: %cst_0 = constant dense<5.000000e+00> : tensor<4xf32>
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// CHECK: %cst_1 = constant dense<2.000000e+00> : tensor<4xf32>
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// CHECK: %cst_2 = constant dense<4.000000e+00> : tensor<4xf32>
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// CHECK: %[[CST:.*]] = constant dense<3.000000e+00> : tensor<f32>
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// CHECK: %[[CST_0:.*]] = constant dense<5.000000e+00> : tensor<4xf32>
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// CHECK: %[[CST_1:.*]] = constant dense<2.000000e+00> : tensor<4xf32>
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// CHECK: %[[CST_2:.*]] = constant dense<4.000000e+00> : tensor<4xf32>
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%5 = "tfl.sub"(%0, %1) {fused_activation_function = "NONE"} : (tensor< f32>, tensor< f32>) -> tensor< f32>
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%6 = "tfl.sub"(%0, %3) {fused_activation_function = "NONE"} : (tensor< f32>, tensor<4xf32>) -> tensor<4xf32>
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@ -75,10 +75,10 @@ func @sub_int() -> (tensor<i32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>) {
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%2 = constant dense< 4> : tensor<4xi32>
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%3 = constant dense<-2> : tensor<4xi32>
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// CHECK: %cst = constant dense<7> : tensor<i32>
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// CHECK: %cst_0 = constant dense<10> : tensor<4xi32>
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// CHECK: %cst_1 = constant dense<3> : tensor<4xi32>
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// CHECK: %cst_2 = constant dense<6> : tensor<4xi32>
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// CHECK: %[[CST:.*]] = constant dense<7> : tensor<i32>
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// CHECK: %[[CST_0:.*]] = constant dense<10> : tensor<4xi32>
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// CHECK: %[[CST_1:.*]] = constant dense<3> : tensor<4xi32>
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// CHECK: %[[CST_2:.*]] = constant dense<6> : tensor<4xi32>
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%5 = "tfl.sub"(%0, %1) {fused_activation_function = "NONE"} : (tensor< i32>, tensor< i32>) -> tensor< i32>
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%6 = "tfl.sub"(%0, %3) {fused_activation_function = "NONE"} : (tensor< i32>, tensor<4xi32>) -> tensor<4xi32>
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@ -96,10 +96,10 @@ func @mul_float() -> (tensor<f32>, tensor<4xf32>, tensor<4xf32>, tensor<4xf32>)
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%2 = constant dense< 3.5> : tensor<4xf32>
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%3 = constant dense<-0.5> : tensor<4xf32>
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// CHECK: %cst = constant dense<6.750000e+00> : tensor<f32>
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// CHECK: %cst_0 = constant dense<-2.250000e+00> : tensor<4xf32>
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// CHECK: %cst_1 = constant dense<5.250000e+00> : tensor<4xf32>
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// CHECK: %cst_2 = constant dense<-1.750000e+00> : tensor<4xf32>
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// CHECK: %[[CST:.*]] = constant dense<6.750000e+00> : tensor<f32>
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// CHECK: %[[CST_0:.*]] = constant dense<-2.250000e+00> : tensor<4xf32>
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// CHECK: %[[CST_1:.*]] = constant dense<5.250000e+00> : tensor<4xf32>
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// CHECK: %[[CST_2:.*]] = constant dense<-1.750000e+00> : tensor<4xf32>
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%5 = "tfl.mul"(%0, %1) {fused_activation_function = "NONE"} : (tensor< f32>, tensor< f32>) -> tensor< f32>
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%6 = "tfl.mul"(%0, %3) {fused_activation_function = "NONE"} : (tensor< f32>, tensor<4xf32>) -> tensor<4xf32>
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@ -170,8 +170,8 @@ func @add_dense_splat_int() -> tensor<4xi32> {
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return %2 : tensor<4xi32>
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// CHECK: %cst = constant dense<[-5, 4, 47, 105]> : tensor<4xi32>
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// CHECK: return %cst
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// CHECK: %[[CST:.*]] = constant dense<[-5, 4, 47, 105]> : tensor<4xi32>
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// CHECK: return %[[CST]]
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}
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// CHECK-LABEL: @add_splat_dense_int
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@ -183,8 +183,8 @@ func @add_splat_dense_int() -> tensor<4xi32> {
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return %2 : tensor<4xi32>
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// CHECK: %cst = constant dense<[-5, 4, 47, 105]> : tensor<4xi32>
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// CHECK: return %cst
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// CHECK: %[[CST:.*]] = constant dense<[-5, 4, 47, 105]> : tensor<4xi32>
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// CHECK: return %[[CST]]
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}
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// CHECK-LABEL: @add_dense_dense_int_same_shape
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@ -196,8 +196,8 @@ func @add_dense_dense_int_same_shape() -> tensor<4xi32> {
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return %2 : tensor<4xi32>
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// CHECK: %cst = constant dense<[5, 22, -2, 98]> : tensor<4xi32>
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// CHECK: return %cst
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// CHECK: %[[CST:.*]] = constant dense<[5, 22, -2, 98]> : tensor<4xi32>
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// CHECK: return %[[CST]]
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}
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// CHECK-LABEL: @add_dense_dense_int_trailing_dim
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@ -212,10 +212,10 @@ func @add_dense_dense_int_trailing_dim() -> (tensor<2x2xi32>, tensor<2x2x2xi32>,
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return %0, %1, %2 : tensor<2x2xi32>, tensor<2x2x2xi32>, tensor<2x2x2xi32>
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// CHECK: %cst = constant dense<{{\[\[}}11, 22], [13, 24]]> : tensor<2x2xi32>
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// CHECK: %cst_0 = constant dense<{{\[\[\[}}2, 3], [5, 6]], {{\[\[}}4, 5], [7, 8]]]> : tensor<2x2x2xi32>
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// CHECK: %cst_1 = constant dense<{{\[\[\[}}11, 21], [12, 22]], {{\[\[}}13, 23], [14, 24]]]> : tensor<2x2x2xi32>
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// CHECK: return %cst, %cst_0, %cst_1
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// CHECK: %[[CST:.*]] = constant dense<{{\[\[}}11, 22], [13, 24]]> : tensor<2x2xi32>
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// CHECK: %[[CST_0:.*]] = constant dense<{{\[\[\[}}2, 3], [5, 6]], {{\[\[}}4, 5], [7, 8]]]> : tensor<2x2x2xi32>
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// CHECK: %[[CST_1:.*]] = constant dense<{{\[\[\[}}11, 21], [12, 22]], {{\[\[}}13, 23], [14, 24]]]> : tensor<2x2x2xi32>
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// CHECK: return %[[CST]], %[[CST_0]], %[[CST_1]]
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}
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// CHECK-LABEL: @add_dense_dense_int_mixing_1_n
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@ -226,8 +226,8 @@ func @add_dense_dense_int_mixing_1_n() -> tensor<2x2xi32> {
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%0 = "tfl.add"(%cst_0, %cst_1) {fused_activation_function = "NONE"} : (tensor<1x2xi32>, tensor<2x1xi32>) -> tensor<2x2xi32>
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return %0 : tensor<2x2xi32>
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// CHECK: %cst = constant dense<{{\[\[}}4, 5], [5, 6]]> : tensor<2x2xi32>
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// CHECK: return %cst
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// CHECK: %[[CST:.*]] = constant dense<{{\[\[}}4, 5], [5, 6]]> : tensor<2x2xi32>
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// CHECK: return %[[CST]]
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}
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// CHECK-LABEL: @add_dense_splat_float
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@ -239,8 +239,8 @@ func @add_dense_splat_float() -> tensor<4xf32> {
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return %2 : tensor<4xf32>
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// CHECK: %cst = constant dense<[-6.500000e+00, 2.000000e+00, 4.550000e+01, 1.075000e+01]> : tensor<4xf32>
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// CHECK: return %cst
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// CHECK: %[[CST:.*]] = constant dense<[-6.500000e+00, 2.000000e+00, 4.550000e+01, 1.075000e+01]> : tensor<4xf32>
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// CHECK: return %[[CST]]
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}
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// CHECK-LABEL: @add_splat_dense_float
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@ -252,8 +252,8 @@ func @add_splat_dense_float() -> tensor<4xf32> {
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return %2 : tensor<4xf32>
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// CHECK: %cst = constant dense<[-6.500000e+00, 2.000000e+00, 4.550000e+01, 1.075000e+01]> : tensor<4xf32>
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// CHECK: return %cst
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// CHECK: %[[CST:.*]] = constant dense<[-6.500000e+00, 2.000000e+00, 4.550000e+01, 1.075000e+01]> : tensor<4xf32>
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// CHECK: return %[[CST]]
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}
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// CHECK-LABEL: @add_dense_dense_float_same_shape
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@ -265,8 +265,8 @@ func @add_dense_dense_float_same_shape() -> (tensor<4xf32>) {
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return %2 : tensor<4xf32>
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// CHECK: %cst = constant dense<[-8.89999961, 1.000000e+00, 3.800000e+01, 9.800000e+01]> : tensor<4xf32>
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// CHECK: return %cst
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// CHECK: %[[CST:.*]] = constant dense<[-8.89999961, 1.000000e+00, 3.800000e+01, 9.800000e+01]> : tensor<4xf32>
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// CHECK: return %[[CST]]
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}
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// CHECK-LABEL: @add_dense_dense_float_trailing_dim
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@ -281,10 +281,10 @@ func @add_dense_dense_float_trailing_dim() -> (tensor<2x2xf32>, tensor<2x2x2xf32
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return %0, %1, %2 : tensor<2x2xf32>, tensor<2x2x2xf32>, tensor<2x2x2xf32>
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// CHECK: %cst = constant dense<{{\[\[}}-4.500000e+00, -2.500000e+00], [8.500000e+00, -8.500000e+00]]> : tensor<2x2xf32>
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// CHECK: %cst_0 = constant dense<{{\[\[\[}}-4.500000e+00, 2.500000e+00], [9.500000e+00, -2.500000e+00]], {{\[\[}}-2.500000e+00, 4.500000e+00], [1.150000e+01, -5.000000e-01]]]> : tensor<2x2x2xf32>
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// CHECK: %cst_1 = constant dense<{{\[\[\[}}2.000000e+00, -3.000000e+00], [3.000000e+00, -2.000000e+00]], {{\[\[}}4.000000e+00, -1.000000e+00], [5.000000e+00, 0.000000e+00]]]> : tensor<2x2x2xf32>
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// CHECK: return %cst, %cst_0, %cst_1
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// CHECK: %[[CST:.*]] = constant dense<{{\[\[}}-4.500000e+00, -2.500000e+00], [8.500000e+00, -8.500000e+00]]> : tensor<2x2xf32>
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// CHECK: %[[CST_0:.*]] = constant dense<{{\[\[\[}}-4.500000e+00, 2.500000e+00], [9.500000e+00, -2.500000e+00]], {{\[\[}}-2.500000e+00, 4.500000e+00], [1.150000e+01, -5.000000e-01]]]> : tensor<2x2x2xf32>
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// CHECK: %[[CST_1:.*]] = constant dense<{{\[\[\[}}2.000000e+00, -3.000000e+00], [3.000000e+00, -2.000000e+00]], {{\[\[}}4.000000e+00, -1.000000e+00], [5.000000e+00, 0.000000e+00]]]> : tensor<2x2x2xf32>
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// CHECK: return %[[CST]], %[[CST_0]], %[[CST_1]]
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}
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// CHECK-LABEL: @add_dense_dense_float_mixfng_1_n
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@ -296,24 +296,24 @@ func @add_dense_dense_float_mixfng_1_n() -> tensor<2x2xf32> {
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return %0 : tensor<2x2xf32>
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// CHECK: %cst = constant dense<{{\[\[}}-1.500000e+00, -5.500000e+00], [5.500000e+00, 1.500000e+00]]> : tensor<2x2xf32>
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// CHECK: return %cst
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// CHECK: %[[CST:.*]] = constant dense<{{\[\[}}-1.500000e+00, -5.500000e+00], [5.500000e+00, 1.500000e+00]]> : tensor<2x2xf32>
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// CHECK: return %[[CST]]
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}
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// CHECK-LABEL: @rank
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func @rank() -> tensor<1xi32> {
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%cst = constant dense<[[1], [2]]> : tensor<2x1xi32>
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// CHECK: [[cst:%.*]] = constant dense<2> : tensor<1xi32>
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// CHECK: return [[cst]]
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// CHECK: %[[CST:.*]] = constant dense<2> : tensor<1xi32>
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// CHECK: return %[[CST]]
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%0 = "tfl.rank"(%cst) : (tensor<2x1xi32>) -> tensor<1xi32>
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return %0 : tensor<1xi32>
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}
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// CHECK-LABEL: @rank_input_known_rank
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func @rank_input_known_rank(%arg0 : tensor<2x1xi32>) -> tensor<1xi32> {
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// CHECK: [[cst:%.*]] = constant dense<2> : tensor<1xi32>
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// CHECK: return [[cst]]
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// CHECK: %[[CST:.*]] = constant dense<2> : tensor<1xi32>
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// CHECK: return %[[CST]]
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%0 = "tfl.rank"(%arg0) : (tensor<2x1xi32>) -> tensor<1xi32>
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return %0 : tensor<1xi32>
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}
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@ -323,8 +323,8 @@ func @reshape() -> tensor<4xi32> {
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%input = constant dense<[[1, 2], [3, 4]]> : tensor<2x2xi32>
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%shape = constant dense<[4]> : tensor<1xi32>
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// CHECK: [[cst:%.*]] = constant dense<[1, 2, 3, 4]> : tensor<4xi32>
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// CHECK: return [[cst]]
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// CHECK: %[[CST:.*]] = constant dense<[1, 2, 3, 4]> : tensor<4xi32>
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// CHECK: return %[[CST]]
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%0 = "tfl.reshape"(%input, %shape) : (tensor<2x2xi32>, tensor<1xi32>) -> tensor<4xi32>
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return %0 : tensor<4xi32>
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}
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@ -334,8 +334,8 @@ func @reshape_dynamic_output() -> tensor<?xi32> {
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%input = constant dense<[[1, 2], [3, 4]]> : tensor<2x2xi32>
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%shape = constant dense<[4]> : tensor<1xi32>
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// CHECK: [[cst:%.*]] = "tfl.pseudo_const"() {value = dense<[1, 2, 3, 4]> : tensor<4xi32>} : () -> tensor<?xi32>
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// CHECK: return [[cst]]
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// CHECK: %[[CST:.*]] = "tfl.pseudo_const"() {value = dense<[1, 2, 3, 4]> : tensor<4xi32>} : () -> tensor<?xi32>
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// CHECK: return %[[CST]]
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%0 = "tfl.reshape"(%input, %shape) : (tensor<2x2xi32>, tensor<1xi32>) -> tensor<?xi32>
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return %0 : tensor<?xi32>
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}
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@ -343,8 +343,8 @@ func @reshape_dynamic_output() -> tensor<?xi32> {
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// CHECK-LABEL: @pseudo_const
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func @pseudo_const() -> tensor<i32> {
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// CHECK: [[cst:%.*]] = constant dense<1> : tensor<i32>
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// CHECK: return [[cst]]
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// CHECK: %[[CST:.*]] = constant dense<1> : tensor<i32>
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// CHECK: return %[[CST]]
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%0 = "tfl.pseudo_const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
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return %0 : tensor<i32>
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}
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@ -356,8 +356,8 @@ func @range_int() -> tensor<?xi32> {
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%cst_1 = constant dense<4> : tensor<i32>
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%cst_2 = constant dense<1> : tensor<i32>
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// CHECK: [[cst:%.*]] = "tfl.pseudo_const"() {value = dense<[0, 1, 2, 3]> : tensor<4xi32>} : () -> tensor<?xi32>
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// CHECK: return [[cst]]
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// CHECK: %[[CST:.*]] = "tfl.pseudo_const"() {value = dense<[0, 1, 2, 3]> : tensor<4xi32>} : () -> tensor<?xi32>
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// CHECK: return %[[CST]]
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%0 = "tfl.range"(%cst, %cst_1, %cst_2) : (tensor<i32>, tensor<i32>, tensor<i32>) -> tensor<?xi32>
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return %0 : tensor<?xi32>
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}
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@ -368,8 +368,8 @@ func @range_float() -> tensor<?xf32> {
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%cst_1 = constant dense<4.0> : tensor<f32>
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%cst_2 = constant dense<1.0> : tensor<f32>
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// CHECK: [[cst:%.*]] = "tfl.pseudo_const"() {value = dense<[0.000000e+00, 1.000000e+00, 2.000000e+00, 3.000000e+00]> : tensor<4xf32>} : () -> tensor<?xf32>
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// CHECK: return [[cst]]
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// CHECK: %[[CST:.*]] = "tfl.pseudo_const"() {value = dense<[0.000000e+00, 1.000000e+00, 2.000000e+00, 3.000000e+00]> : tensor<4xf32>} : () -> tensor<?xf32>
|
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// CHECK: return %[[CST]]
|
||||
%0 = "tfl.range"(%cst, %cst_1, %cst_2) : (tensor<f32>, tensor<f32>, tensor<f32>) -> tensor<?xf32>
|
||||
return %0 : tensor<?xf32>
|
||||
}
|
||||
@ -381,8 +381,8 @@ func @range_float_neg_delta() -> tensor<?xf32> {
|
||||
%cst_1 = constant dense<-4.0> : tensor<f32>
|
||||
%cst_2 = constant dense<-1.0> : tensor<f32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = "tfl.pseudo_const"() {value = dense<[0.000000e+00, -1.000000e+00, -2.000000e+00, -3.000000e+00]> : tensor<4xf32>} : () -> tensor<?xf32>
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: %[[CST:.*]] = "tfl.pseudo_const"() {value = dense<[0.000000e+00, -1.000000e+00, -2.000000e+00, -3.000000e+00]> : tensor<4xf32>} : () -> tensor<?xf32>
|
||||
// CHECK: return %[[CST]]
|
||||
%0 = "tfl.range"(%cst, %cst_1, %cst_2) : (tensor<f32>, tensor<f32>, tensor<f32>) -> tensor<?xf32>
|
||||
return %0 : tensor<?xf32>
|
||||
}
|
||||
@ -393,8 +393,8 @@ func @range_float_nonzero_base() -> tensor<?xf32> {
|
||||
%cst_1 = constant dense<7.0> : tensor<f32>
|
||||
%cst_2 = constant dense<1.5> : tensor<f32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = "tfl.pseudo_const"() {value = dense<[2.000000e+00, 3.500000e+00, 5.000000e+00, 6.500000e+00]> : tensor<4xf32>} : () -> tensor<?xf32>
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: %[[CST:.*]] = "tfl.pseudo_const"() {value = dense<[2.000000e+00, 3.500000e+00, 5.000000e+00, 6.500000e+00]> : tensor<4xf32>} : () -> tensor<?xf32>
|
||||
// CHECK: return %[[CST]]
|
||||
%0 = "tfl.range"(%cst, %cst_1, %cst_2) : (tensor<f32>, tensor<f32>, tensor<f32>) -> tensor<?xf32>
|
||||
return %0 : tensor<?xf32>
|
||||
}
|
||||
@ -414,8 +414,8 @@ func @transpose_1d() -> tensor<3xi32> {
|
||||
%cst = constant dense<[1, 2, 3]> : tensor<3xi32>
|
||||
%cst_perm = constant dense<0> : tensor<1xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = constant dense<{{\[}}1, 2, 3]> : tensor<3xi32>
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: %[[CST:.*]] = constant dense<{{\[}}1, 2, 3]> : tensor<3xi32>
|
||||
// CHECK: return %[[CST]]
|
||||
%0 = "tfl.transpose"(%cst, %cst_perm) : (tensor<3xi32>, tensor<1xi32>) -> tensor<3xi32>
|
||||
return %0 : tensor<3xi32>
|
||||
}
|
||||
@ -425,8 +425,8 @@ func @transpose_dynamic() -> tensor<?xi32> {
|
||||
%cst = constant dense<[1, 2, 3]> : tensor<3xi32>
|
||||
%cst_perm = constant dense<0> : tensor<1xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = "tfl.pseudo_const"() {value = dense<{{\[}}1, 2, 3]> : tensor<3xi32>} : () -> tensor<?xi32>
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: %[[CST:.*]] = "tfl.pseudo_const"() {value = dense<{{\[}}1, 2, 3]> : tensor<3xi32>} : () -> tensor<?xi32>
|
||||
// CHECK: return %[[CST]]
|
||||
%0 = "tfl.transpose"(%cst, %cst_perm) : (tensor<3xi32>, tensor<1xi32>) -> tensor<?xi32>
|
||||
return %0 : tensor<?xi32>
|
||||
}
|
||||
@ -436,8 +436,8 @@ func @transpose_2d() -> tensor<2x2xi32> {
|
||||
%cst = constant dense<[[0, 1], [2, 3]]> : tensor<2x2xi32>
|
||||
%cst_perm = constant dense<[1, 0]> : tensor<2xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = constant dense<{{\[\[}}0, 2], {{\[}}1, 3]]> : tensor<2x2xi32>
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: %[[CST:.*]] = constant dense<{{\[\[}}0, 2], {{\[}}1, 3]]> : tensor<2x2xi32>
|
||||
// CHECK: return %[[CST]]
|
||||
%0 = "tfl.transpose"(%cst, %cst_perm) : (tensor<2x2xi32>, tensor<2xi32>) -> tensor<2x2xi32>
|
||||
return %0 : tensor<2x2xi32>
|
||||
}
|
||||
@ -447,8 +447,8 @@ func @transpose_2d_identity() -> tensor<2x2xi32> {
|
||||
%cst = constant dense<[[0, 1], [2, 3]]> : tensor<2x2xi32>
|
||||
%cst_perm = constant dense<[0, 1]> : tensor<2xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = constant dense<{{\[\[}}0, 1], {{\[}}2, 3]]> : tensor<2x2xi32>
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: %[[CST:.*]] = constant dense<{{\[\[}}0, 1], {{\[}}2, 3]]> : tensor<2x2xi32>
|
||||
// CHECK: return %[[CST]]
|
||||
%0 = "tfl.transpose"(%cst, %cst_perm) : (tensor<2x2xi32>, tensor<2xi32>) -> tensor<2x2xi32>
|
||||
return %0 : tensor<2x2xi32>
|
||||
}
|
||||
@ -460,8 +460,8 @@ func @transpose_3d() -> tensor<4x2x3xi32> {
|
||||
%cst = constant dense<[[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]], [[12, 13, 14, 15], [16, 17, 18, 19], [20, 21, 22, 23]]]> : tensor<2x3x4xi32>
|
||||
%cst_perm = constant dense<[2, 0, 1]> : tensor<3xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = constant dense<{{\[\[\[}}0, 4, 8], {{\[}}12, 16, 20]], {{\[\[}}1, 5, 9], {{\[}}13, 17, 21]], {{\[\[}}2, 6, 10], {{\[}}14, 18, 22]], {{\[\[}}3, 7, 11], {{\[}}15, 19, 23]]]> : tensor<4x2x3xi32>
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: %[[CST:.*]] = constant dense<{{\[\[\[}}0, 4, 8], {{\[}}12, 16, 20]], {{\[\[}}1, 5, 9], {{\[}}13, 17, 21]], {{\[\[}}2, 6, 10], {{\[}}14, 18, 22]], {{\[\[}}3, 7, 11], {{\[}}15, 19, 23]]]> : tensor<4x2x3xi32>
|
||||
// CHECK: return %[[CST]]
|
||||
%0 = "tfl.transpose"(%cst, %cst_perm) : (tensor<2x3x4xi32>, tensor<3xi32>) -> tensor<4x2x3xi32>
|
||||
return %0 : tensor<4x2x3xi32>
|
||||
}
|
||||
@ -473,8 +473,8 @@ func @ConstantFoldBinaryOpDynamicOutput() -> tensor<?xi32> {
|
||||
%87 = "tfl.sub"(%cst_0, %cst) {fused_activation_function = "NONE"} : (tensor<?xi32>, tensor<i32>) -> tensor<?xi32>
|
||||
return %87 : tensor<?xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = "tfl.pseudo_const"() {value = dense<[-5, 0]> : tensor<2xi32>} : () -> tensor<?xi32>
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: %[[CST:.*]] = "tfl.pseudo_const"() {value = dense<[-5, 0]> : tensor<2xi32>} : () -> tensor<?xi32>
|
||||
// CHECK: return %[[CST]]
|
||||
}
|
||||
|
||||
// CHECK-LABEL: @add_dense_dense_int_same_shape_dynamic
|
||||
@ -486,8 +486,8 @@ func @add_dense_dense_int_same_shape_dynamic() -> tensor<?xi32> {
|
||||
|
||||
return %2 : tensor<?xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = "tfl.pseudo_const"() {value = dense<[5, 22, -2, 98]> : tensor<4xi32>} : () -> tensor<?xi32>
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: %[[CST:.*]] = "tfl.pseudo_const"() {value = dense<[5, 22, -2, 98]> : tensor<4xi32>} : () -> tensor<?xi32>
|
||||
// CHECK: return %[[CST]]
|
||||
}
|
||||
|
||||
// CHECK-LABEL: @concat_2_tensors_1_empty
|
||||
@ -497,8 +497,8 @@ func @concat_2_tensors_1_empty() -> tensor<2xi32> {
|
||||
%3 = "tfl.concatenation"(%1, %2) {axis = 0 : i32, fused_activation_function = "NONE"} : (tensor<2xi32>, tensor<0xi32>) -> tensor<2xi32>
|
||||
return %3 : tensor<2xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = constant dense<1> : tensor<2xi32>
|
||||
// CHECK: return [[cst]] : tensor<2xi32>
|
||||
// CHECK: %[[CST:.*]] = constant dense<1> : tensor<2xi32>
|
||||
// CHECK: return %[[CST]] : tensor<2xi32>
|
||||
}
|
||||
|
||||
// CHECK-LABEL: @concat_3_tensors_1_empty
|
||||
@ -509,7 +509,7 @@ func @concat_3_tensors_1_empty() -> tensor<?xi32> {
|
||||
%3 = "tfl.concatenation"(%0, %1, %2) {axis = 0 : i32, fused_activation_function = "NONE"} : (tensor<2xi32>, tensor<2xi32>, tensor<0xi32>) -> tensor<?xi32>
|
||||
return %3 : tensor<?xi32>
|
||||
|
||||
// CHECK: %0 = "tfl.concatenation"(%cst, %cst) {axis = 0 : i32, fused_activation_function = "NONE"}
|
||||
// CHECK: %0 = "tfl.concatenation"(%[[CST]], %[[CST]]) {axis = 0 : i32, fused_activation_function = "NONE"}
|
||||
// CHECK: return %0 : tensor<?xi32>
|
||||
}
|
||||
|
||||
@ -520,10 +520,10 @@ func @concatConstantTensorsFirstDim() -> tensor<2x2x3xi32> {
|
||||
%0 = "tfl.concatenation"(%cst_0, %cst_1) {axis = 0 : i32, fused_activation_function = "NONE"} : (tensor<1x2x3xi32>, tensor<1x2x3xi32>) -> tensor<2x2x3xi32>
|
||||
return %0 : tensor<2x2x3xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = constant dense<[{{\[}}{{\[}}0, 0, 0], {{\[}}0, 0, 0]], {{\[}}{{\[}}1, 1, 1], {{\[}}1, 1, 1]]]> : tensor<2x2x3xi32>
|
||||
// CHECK: %[[CST:.*]] = constant dense<[{{\[}}{{\[}}0, 0, 0], {{\[}}0, 0, 0]], {{\[}}{{\[}}1, 1, 1], {{\[}}1, 1, 1]]]> : tensor<2x2x3xi32>
|
||||
// CHECK-NOT: constant-dense
|
||||
// CHECK-NOT: "tfl.concatenation"
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: return %[[CST]]
|
||||
}
|
||||
|
||||
// CHECK-LABEL: @concatConstantTensorsMiddleDim
|
||||
@ -533,10 +533,10 @@ func @concatConstantTensorsMiddleDim() -> tensor<1x4x3xi32> {
|
||||
%0 = "tfl.concatenation"(%cst_0, %cst_1) {axis = 1 : i32, fused_activation_function = "NONE"} : (tensor<1x2x3xi32>, tensor<1x2x3xi32>) -> tensor<1x4x3xi32>
|
||||
return %0 : tensor<1x4x3xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = constant dense<[{{\[}}{{\[}}0, 0, 0], {{\[}}0, 0, 0], {{\[}}1, 1, 1], {{\[}}1, 1, 1]]]> : tensor<1x4x3xi32>
|
||||
// CHECK: %[[CST:.*]] = constant dense<[{{\[}}{{\[}}0, 0, 0], {{\[}}0, 0, 0], {{\[}}1, 1, 1], {{\[}}1, 1, 1]]]> : tensor<1x4x3xi32>
|
||||
// CHECK-NOT: constant-dense
|
||||
// CHECK-NOT: "tfl.concatenation"
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: return %[[CST]]
|
||||
}
|
||||
|
||||
// CHECK-LABEL: @concatConstantTensorsLastDim
|
||||
@ -546,10 +546,10 @@ func @concatConstantTensorsLastDim() -> tensor<1x2x6xi32> {
|
||||
%0 = "tfl.concatenation"(%cst_0, %cst_1) {axis = 2 : i32, fused_activation_function = "NONE"} : (tensor<1x2x3xi32>, tensor<1x2x3xi32>) -> tensor<1x2x6xi32>
|
||||
return %0 : tensor<1x2x6xi32>
|
||||
|
||||
// CHECK: [[cst:%.*]] = constant dense<[{{\[}}{{\[}}0, 0, 0, 1, 1, 1], {{\[}}0, 0, 0, 1, 1, 1]]]> : tensor<1x2x6xi32>
|
||||
// CHECK: %[[CST:.*]] = constant dense<[{{\[}}{{\[}}0, 0, 0, 1, 1, 1], {{\[}}0, 0, 0, 1, 1, 1]]]> : tensor<1x2x6xi32>
|
||||
// CHECK-NOT: constant-dense
|
||||
// CHECK-NOT: "tfl.concatenation"
|
||||
// CHECK: return [[cst]]
|
||||
// CHECK: return %[[CST]]
|
||||
}
|
||||
|
||||
// CHECK-LABEL: @div_dense_dense_float_mixfng_1_n
|
||||
@ -561,8 +561,8 @@ func @div_dense_dense_float_mixfng_1_n() -> tensor<2x2xf32> {
|
||||
|
||||
return %0 : tensor<2x2xf32>
|
||||
|
||||
// CHECK: %cst = constant dense<{{\[\[}}-5.000000e-01, 0.833333313], [3.750000e-01, -6.250000e-01]]> : tensor<2x2xf32>
|
||||
// CHECK: return %cst
|
||||
// CHECK: %[[CST:.*]] = constant dense<{{\[\[}}-5.000000e-01, 0.833333313], [3.750000e-01, -6.250000e-01]]> : tensor<2x2xf32>
|
||||
// CHECK: return %[[CST]]
|
||||
}
|
||||
|
||||
// CHECK-LABEL: @div_dense_different_rank
|
||||
@ -574,6 +574,6 @@ func @div_dense_different_rank() -> tensor<1x2x2xf32> {
|
||||
|
||||
return %0 : tensor<1x2x2xf32>
|
||||
|
||||
// CHECK: %cst = constant dense<[{{\[}}{{\[}}5.000000e-01, 0.333333343], [1.000000e+00, 0.666666686]]]> : tensor<1x2x2xf32>
|
||||
// CHECK: return %cst
|
||||
// CHECK: %[[CST:.*]] = constant dense<[{{\[}}{{\[}}5.000000e-01, 0.333333343], [1.000000e+00, 0.666666686]]]> : tensor<1x2x2xf32>
|
||||
// CHECK: return %[[CST]]
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user