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[tf-frontend] fix numpy version
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@Vremold
Vremold committed Jul 5, 2024
1 parent 80160ed commit 5aeb24d
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Showing 2 changed files with 38 additions and 34 deletions.
1 change: 1 addition & 0 deletions frontends/tf-frontend/scripts/build_and_test.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@ PROJ_DIR="$CUR_DIR/.."
bash $PROJ_DIR/scripts/prepare.sh

pushd $PROJ_DIR
python3 -m pip install numpy==1.26.4 --force-reinstall
python3 -m pip install /data00/mhlo_libraries/mhlo_tools-1.4.0-cp39-cp39-linux_x86_64.whl
$PROJ_DIR/bazel --output_user_root=./build build --experimental_ui_max_stdouterr_bytes=-1 //tools:tf-frontend //tools:tf-ext-opt
$PROJ_DIR/bazel --output_user_root=./build test --experimental_ui_max_stdouterr_bytes=-1 --test_output=errors //tf_mlir_ext/tests:all --java_runtime_version=remotejdk_11
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71 changes: 37 additions & 34 deletions frontends/tf-frontend/tf_mlir_ext/numerical/rewrite_to_custom_call.mlir
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Original file line number Diff line number Diff line change
Expand Up @@ -245,12 +245,12 @@ func.func @layer_norm_without_gamma(%arg0: tensor<32x64xf32>) -> tensor<32x64xf3
%7 = "tf.AddV2"(%6, %cst_3) {device = ""} : (tensor<32x64xf32>, tensor<64xf32>) -> tensor<32x64xf32>
func.return %7 : tensor<32x64xf32>
}
// CHECK-LABEL: func.func @layer_norm_without_gamma(%arg0: tensor<32x64xf32>) -> tensor<32x64xf32> {
// CHECK-LABEL: %cst = "tf.Const"() <{value = dense<1.000000e+00> : tensor<64xf32>}> : () -> tensor<64xf32>
// CHECK-LABEL: %cst_0 = "tf.Const"() <{value = dense<[-1.916500e-02, -1.800540e-03, -7.980340e-03, -1.962280e-02, 1.242070e-02, -1.342770e-02, -2.662660e-03, 9.689330e-03, 1.054380e-02, -1.081470e-03, -4.814150e-03, -1.013180e-02, -1.199340e-02, -8.544920e-03, -1.773070e-02, -1.400760e-02, -1.400760e-02, 0.00753783993, 1.226810e-02, -1.586910e-02, 3.944400e-03, -1.486210e-02, 1.170350e-02, -6.538390e-03, 1.702880e-02, 2.510070e-03, -1.387020e-02, 1.486210e-02, 1.071930e-03, -1.185610e-02, -6.973270e-03, 5.813600e-03, 7.827750e-03, -1.486210e-02, -6.828300e-03, -1.271060e-02, -3.234860e-03, -6.248470e-03, 2.079010e-03, -7.400510e-03, 1.414490e-02, -8.544920e-03, 2.796170e-03, 9.109490e-03, -9.262080e-03, -3.633500e-04, -1.760860e-02, 1.414490e-02, 5.378720e-03, -1.242070e-02, -7.255550e-03, -1.629640e-02, 9.552000e-03, -1.300050e-02, 1.499940e-02, -1.199340e-02, 9.262080e-03, -2.198220e-04, 9.288780e-04, 5.378720e-03, 6.675720e-03, 1.457210e-02, 8.255000e-03, -0.00883482955]> : tensor<64xf32>}> : () -> tensor<64xf32>
// CHECK-LABEL: %0 = mhlo.custom_call @byteir.layer_norm(%arg0, %cst, %cst_0) {backend_config = "", byteir_attrs = {axis = [1], epsilon = 1.0132799843631801E-6 : f64}} : (tensor<32x64xf32>, tensor<64xf32>, tensor<64xf32>) -> tensor<32x64xf32>
// CHECK-LABEL: return %0 : tensor<32x64xf32>
// CHECK-LABEL: }
// CHECK-LABEL: func.func @layer_norm_without_gamma(%arg0: tensor<32x64xf32>) -> tensor<32x64xf32> {
// CHECK-DAG: "tf.Const"() <{value = dense<[-1.916500e-02, -1.800540e-03, -7.980340e-03, -1.962280e-02, 1.242070e-02, -1.342770e-02, -2.662660e-03, 9.689330e-03, 1.054380e-02, -1.081470e-03, -4.814150e-03, -1.013180e-02, -1.199340e-02, -8.544920e-03, -1.773070e-02, -1.400760e-02, -1.400760e-02, 0.00753783993, 1.226810e-02, -1.586910e-02, 3.944400e-03, -1.486210e-02, 1.170350e-02, -6.538390e-03, 1.702880e-02, 2.510070e-03, -1.387020e-02, 1.486210e-02, 1.071930e-03, -1.185610e-02, -6.973270e-03, 5.813600e-03, 7.827750e-03, -1.486210e-02, -6.828300e-03, -1.271060e-02, -3.234860e-03, -6.248470e-03, 2.079010e-03, -7.400510e-03, 1.414490e-02, -8.544920e-03, 2.796170e-03, 9.109490e-03, -9.262080e-03, -3.633500e-04, -1.760860e-02, 1.414490e-02, 5.378720e-03, -1.242070e-02, -7.255550e-03, -1.629640e-02, 9.552000e-03, -1.300050e-02, 1.499940e-02, -1.199340e-02, 9.262080e-03, -2.198220e-04, 9.288780e-04, 5.378720e-03, 6.675720e-03, 1.457210e-02, 8.255000e-03, -0.00883482955]> : tensor<64xf32>}> : () -> tensor<64xf32>
// CHECK-DAG: "tf.Const"() <{value = dense<1.000000e+00> : tensor<64xf32>}> : () -> tensor<64xf32>
// CHECK: mhlo.custom_call
// CHECK-SAME: @byteir.layer_norm
// CHECK-SAME: byteir_attrs = {axis = [1], epsilon = 1.0132799843631801E-6 : f64}}

func.func @layer_norm_without_beta(%arg0: tensor<512x128xf16>) -> tensor<512x128xf16> {
%cst_1 = "tf.Const"() {value = dense<"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tensor<128xf16>} : () -> tensor<128xf16>
Expand All @@ -268,11 +268,11 @@ func.func @layer_norm_without_beta(%arg0: tensor<512x128xf16>) -> tensor<512x128
func.return %8 : tensor<512x128xf16>
}
// CHECK-LABEL: func.func @layer_norm_without_beta(%arg0: tensor<512x128xf16>) -> tensor<512x128xf16> {
// CHECH-DAG: "tf.Const"() <{value = dense<0.000000e+00> : tensor<128xf16>}> : () -> tensor<128xf16>
// CHECK-DAG: "tf.Const"() <{value = dense<"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tensor<128xf16>}> : () -> tensor<128xf16>
// CHECK: mhlo.custom_call
// CHECK-SAME: @byteir.layer_norm
// CHECK-SAME: byteir_attrs = {axis = [1], epsilon = 1.0001659393310547E-4 : f64}
// CHECH-DAG: "tf.Const"() <{value = dense<0.000000e+00> : tensor<128xf16>}> : () -> tensor<128xf16>
// CHECK-DAG: "tf.Const"() <{value = dense<"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tensor<128xf16>}> : () -> tensor<128xf16>
// CHECK: mhlo.custom_call
// CHECK-SAME: @byteir.layer_norm
// CHECK-SAME: byteir_attrs = {axis = [1], epsilon = 1.0001659393310547E-4 : f64}

func.func @layer_norm_multi_dim(%arg0: tensor<2x8x4xf32>) -> tensor<2x8x4xf32> {
%cst = "tf.Const"() <{value = dense<-1> : tensor<1xi32>}> : () -> tensor<1xi32>
Expand All @@ -292,12 +292,13 @@ func.func @layer_norm_multi_dim(%arg0: tensor<2x8x4xf32>) -> tensor<2x8x4xf32> {
func.return %9 : tensor<2x8x4xf32>
}
// CHECK-LABEL: func.func @layer_norm_multi_dim(%arg0: tensor<2x8x4xf32>) -> tensor<2x8x4xf32> {
// CHECK: %0 = "tf.Reshape"(%arg0, %cst_1) : (tensor<2x8x4xf32>, tensor<2xi64>) -> tensor<16x4xf32>
// CHECK-NEXT: %1 = mhlo.custom_call @byteir.layer_norm(%0, %cst, %cst_0) {backend_config = "", byteir_attrs = {axis = [1], epsilon = 9.9999999747524271E-7 : f64}} : (tensor<16x4xf32>
// CHECK-NEXT: %2 = "tf.Reshape"(%1, %cst_2) : (tensor<16x4xf32>, tensor<3xi64>) -> tensor<2x8x4xf32>
// CHECK-NEXT: %3 = "tf.Mul"(%2, %cst_3) : (tensor<2x8x4xf32>, tensor<2x1x4xf32>) -> tensor<2x8x4xf32>
// CHECK-NEXT: %4 = "tf.Add"(%3, %cst_4) : (tensor<2x8x4xf32>, tensor<2x1x4xf32>) -> tensor<2x8x4xf32>
// CHECK-NEXT: return %4 : tensor<2x8x4xf32>
// CHECK: "tf.Reshape"
// CHECK: mhlo.custom_call
// CHECK-SAME: @byteir.layer_norm
// CHECK-SAME: byteir_attrs = {axis = [1], epsilon = 9.9999999747524271E-7 : f64}}
// CHECK-NEXT: "tf.Reshape"
// CHECK-NEXT: "tf.Mul"
// CHECK-NEXT: "tf.Add"

func.func @layer_norm_multi_dim_v2(%arg0: tensor<2x8x4xf32>) -> tensor<2x8x4xf32> {
%cst = "tf.Const"() <{value = dense<2> : tensor<1xi32>}> : () -> tensor<1xi32>
Expand All @@ -317,12 +318,13 @@ func.func @layer_norm_multi_dim_v2(%arg0: tensor<2x8x4xf32>) -> tensor<2x8x4xf32
func.return %9 : tensor<2x8x4xf32>
}
// CHECK-LABEL: func.func @layer_norm_multi_dim_v2(%arg0: tensor<2x8x4xf32>) -> tensor<2x8x4xf32> {
// CHECK: %0 = "tf.Reshape"(%arg0, %cst_1) : (tensor<2x8x4xf32>, tensor<2xi64>) -> tensor<16x4xf32>
// CHECK-NEXT: %1 = mhlo.custom_call @byteir.layer_norm(%0, %cst, %cst_0) {backend_config = "", byteir_attrs = {axis = [1], epsilon = 9.9999999747524271E-7 : f64}} : (tensor<16x4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<16x4xf32>
// CHECK-NEXT: %2 = "tf.Reshape"(%1, %cst_2) : (tensor<16x4xf32>, tensor<3xi64>) -> tensor<2x8x4xf32>
// CHECK-NEXT: %3 = "tf.Mul"(%2, %cst_3) : (tensor<2x8x4xf32>, tensor<2x1x4xf32>) -> tensor<2x8x4xf32>
// CHECK-NEXT: %4 = "tf.Add"(%3, %cst_4) : (tensor<2x8x4xf32>, tensor<2x1x4xf32>) -> tensor<2x8x4xf32>
// CHECK-NEXT: return %4 : tensor<2x8x4xf32>
// CHECK: "tf.Reshape"
// CHECK-NEXT: mhlo.custom_call
// CHECK-SAME: @byteir.layer_norm
// CHECK-SAME: byteir_attrs = {axis = [1], epsilon = 9.9999999747524271E-7 : f64}}
// CHECK-NEXT: "tf.Reshape"
// CHECK-NEXT: "tf.Mul"
// CHECK-NEXT: "tf.Add"

func.func @layer_norm_swap_add(%arg0: tensor<2x32x3xf32>) -> tensor<2x32x3xf32> {
%cst_15 = "tf.Const"() {value = dense<9.99999997E-7> : tensor<f32>} : () -> tensor<f32>
Expand All @@ -342,8 +344,9 @@ func.func @layer_norm_swap_add(%arg0: tensor<2x32x3xf32>) -> tensor<2x32x3xf32>
return %9 : tensor<2x32x3xf32>
}
// CHECK-LABEL: @layer_norm_swap_add
// CHECK: mhlo.custom_call
// CHECK-SAME: @byteir.layer_norm
// CHECK: mhlo.custom_call
// CHECK-SAME: @byteir.layer_norm
// CHECK-SAME: byteir_attrs = {axis = [2], epsilon = 9.9999999747524271E-7 : f64}}

func.func @layer_norm_swap_mul(%arg0: tensor<1x16x3xf32>) -> tensor<1x16x3xf32> {
%cst_685 = "tf.Const"() {value = dense<9.99999997E-7> : tensor<f32>} : () -> tensor<f32>
Expand Down Expand Up @@ -404,8 +407,8 @@ func.func @layer_norm_V2(%arg0: tensor<1x32x3xf32>) -> tensor<1x32x3xf32> {
func.return %8 : tensor<1x32x3xf32>
}
// CHECK-LABEL: func.func @layer_norm_V2(%arg0: tensor<1x32x3xf32>) -> tensor<1x32x3xf32> {
// CHECK-NEXT: %cst = "tf.Const"() <{value = dense<[0.0401659757, -0.11370486, 0.432680517]> : tensor<3xf32>}> : () -> tensor<3xf32>
// CHECK-NEXT: %cst_0 = "tf.Const"() <{value = dense<[0.445568085, 0.45303449, 3.227140e-01]> : tensor<3xf32>}> : () -> tensor<3xf32>
// CHECK-NEXT: "tf.Const"() <{value = dense<[0.0401659757, -0.11370486, 0.432680517]> : tensor<3xf32>}> : () -> tensor<3xf32>
// CHECK-NEXT: "tf.Const"() <{value = dense<[0.445568085, 0.45303449, 3.227140e-01]> : tensor<3xf32>}> : () -> tensor<3xf32>
// CHECK: mhlo.custom_call
// CHECK-SAME: @byteir.layer_norm
// CHECK-SAME: byteir_attrs = {axis = [2], epsilon = 9.9999999747524271E-7 : f64}
Expand Down Expand Up @@ -490,8 +493,8 @@ func.func @layer_norm_with_cast(%79: tensor<150x3xf16>) -> tensor<150x3xf16> {
return %91 : tensor<150x3xf16>
}
// CHECK-LABEL: func.func @layer_norm_with_cast(%arg0: tensor<150x3xf16>) -> tensor<150x3xf16> {
// CHECK-NEXT: %cst = "tf.Const"() <{value = dense<[4.016110e-02, -1.137080e-01, 4.326170e-01]> : tensor<3xf16>}> : () -> tensor<3xf16>
// CHECK-NEXT: %cst_0 = "tf.Const"() <{value = dense<[4.455570e-01, 4.531250e-01, 3.227540e-01]> : tensor<3xf16>}> : () -> tensor<3xf16>
// CHECK-NEXT: "tf.Const"() <{value = dense<[4.016110e-02, -1.137080e-01, 4.326170e-01]> : tensor<3xf16>}> : () -> tensor<3xf16>
// CHECK-NEXT: "tf.Const"() <{value = dense<[4.455570e-01, 4.531250e-01, 3.227540e-01]> : tensor<3xf16>}> : () -> tensor<3xf16>
// CHECK: mhlo.custom_call
// CHECK-SAME: @byteir.layer_norm
// CHECK-SAME: byteir_attrs = {axis = [1], epsilon = 1.0132789611816406E-6 : f64}
Expand All @@ -517,8 +520,8 @@ func.func @layer_norm_with_cast_v2(%79: tensor<150x3xf16>) -> tensor<150x3xf16>
return %92 : tensor<150x3xf16>
}
// CHECK-LABEL: func.func @layer_norm_with_cast_v2(%arg0: tensor<150x3xf16>) -> tensor<150x3xf16> {
// CHECK-NEXT: %cst = "tf.Const"() <{value = dense<[4.016110e-02, -1.137080e-01, 4.326170e-01]> : tensor<3xf16>}> : () -> tensor<3xf16>
// CHECK-NEXT: %cst_0 = "tf.Const"() <{value = dense<[4.455570e-01, 4.531250e-01, 3.227540e-01]> : tensor<3xf16>}> : () -> tensor<3xf16>
// CHECK-NEXT: "tf.Const"() <{value = dense<[4.016110e-02, -1.137080e-01, 4.326170e-01]> : tensor<3xf16>}> : () -> tensor<3xf16>
// CHECK-NEXT: "tf.Const"() <{value = dense<[4.455570e-01, 4.531250e-01, 3.227540e-01]> : tensor<3xf16>}> : () -> tensor<3xf16>
// CHECK: mhlo.custom_call
// CHECK-SAME: @byteir.layer_norm
// CHECK-SAME: byteir_attrs = {axis = [1], epsilon = 1.0132789611816406E-6 : f64}
Expand Down Expand Up @@ -574,9 +577,9 @@ func.func @l2_norm_V1_with_multiplyer(%arg0: tensor<2x4x8xf32>) -> tensor<2x4x8x
func.return %5 : tensor<2x4x8xf32>
}
// CHECK-LABEL: func.func @l2_norm_V1_with_multiplyer(%arg0: tensor<2x4x8xf32>) -> tensor<2x4x8xf32> {
// CHECK-NEXT: %0 = mhlo.constant dense<9.34093475> : tensor<2x4x8xf32>
// CHECK-NEXT: %1 = mhlo.custom_call @byteir.l2_norm(%arg0) {backend_config = "", byteir_attrs = {axis = [2], eps_outside_sqrt = false, epsilon = 9.999999960041972E-13 : f64}} : (tensor<2x4x8xf32>) -> tensor<2x4
// CHECK-NEXT: %2 = mhlo.multiply %1, %0 : tensor<2x4x8xf32>
// CHECK-NEXT: mhlo.constant dense<9.34093475> : tensor<2x4x8xf32>
// CHECK-NEXT: mhlo.custom_call @byteir.l2_norm(%arg0) {backend_config = "", byteir_attrs = {axis = [2], eps_outside_sqrt = false, epsilon = 9.999999960041972E-13 : f64}} : (tensor<2x4x8xf32>) -> tensor<2x4
// CHECK-NEXT: mhlo.multiply

func.func @l2_norm_V1_swap_mul(%54: tensor<1x64xf32>) -> tensor<1x64xf32> {
%cst_0 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
Expand Down

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