From 5c79b676279b4b1a6707cb8259c46fffe35e541f Mon Sep 17 00:00:00 2001
From: Nolwen <nolwen.huet@imacs.polytechnique.fr>
Date: Fri, 15 Dec 2023 16:36:47 +0100
Subject: [PATCH] Xfail pytorch tests with conv2d/maxpooling + float16 + CPU

---
 tests/test_backward_conv.py |  4 ++++
 tests/test_conv.py          |  8 ++++++++
 tests/test_pooling.py       |  5 +++++
 tests/test_utils_conv.py    | 11 +++++++++--
 4 files changed, 26 insertions(+), 2 deletions(-)

diff --git a/tests/test_backward_conv.py b/tests/test_backward_conv.py
index 788b84f1..f51c031f 100644
--- a/tests/test_backward_conv.py
+++ b/tests/test_backward_conv.py
@@ -10,6 +10,10 @@
 
 
 def test_Decomon_conv_box(data_format, padding, use_bias, mode, floatx, decimal, helpers):
+    # xfail unavailable combinations
+    if floatx == 16 and keras_config.backend() == "torch":
+        pytest.xfail("Pytorch does not implement conv2d for float16")
+
     if data_format == "channels_first" and not helpers.in_GPU_mode():
         pytest.skip("data format 'channels first' is possible only in GPU mode")
 
diff --git a/tests/test_conv.py b/tests/test_conv.py
index 5f98ccbb..24518b5f 100644
--- a/tests/test_conv.py
+++ b/tests/test_conv.py
@@ -12,6 +12,10 @@
 
 
 def test_Decomon_conv_box(data_format, mode, dc_decomp, floatx, decimal, helpers):
+    # xfail unavailable combinations
+    if floatx == 16 and keras_config.backend() == "torch":
+        pytest.xfail("Pytorch does not implement conv2d for float16")
+
     if data_format == "channels_first" and not helpers.in_GPU_mode():
         pytest.skip("data format 'channels first' is possible only in GPU mode")
 
@@ -63,6 +67,10 @@ def test_Decomon_conv_box(data_format, mode, dc_decomp, floatx, decimal, helpers
 
 
 def test_Decomon_conv_to_decomon_box(shared, floatx, dc_decomp, helpers):
+    # xfail unavailable combinations
+    if floatx == 16 and keras_config.backend() == "torch":
+        pytest.xfail("Pytorch does not implement conv2d for float16")
+
     data_format = "channels_last"
     odd, m_0, m_1 = 0, 0, 1
     dc_decomp = True
diff --git a/tests/test_pooling.py b/tests/test_pooling.py
index f87cbfad..a0cdf295 100644
--- a/tests/test_pooling.py
+++ b/tests/test_pooling.py
@@ -1,10 +1,15 @@
 import keras.config as keras_config
+import pytest
 from keras.layers import MaxPooling2D
 
 from decomon.layers.maxpooling import DecomonMaxPooling2D
 
 
 def test_MaxPooling2D_box(mode, floatx, decimal, helpers):
+    # xfail unavailable combinations
+    # if floatx == 16 and keras_config.backend() == "torch":
+    #     pytest.xfail("Pytorch does not implement maxpooling for float16")
+
     odd, m_0, m_1 = 0, 0, 1
     data_format = "channels_last"
     dc_decomp = True
diff --git a/tests/test_utils_conv.py b/tests/test_utils_conv.py
index 0f0979d3..7d9beb1a 100644
--- a/tests/test_utils_conv.py
+++ b/tests/test_utils_conv.py
@@ -1,6 +1,5 @@
 # Test unit for decomon with Dense layers
-
-
+import keras.config
 import keras.ops as K
 import numpy as np
 import pytest
@@ -13,6 +12,10 @@
 
 
 def test_toeplitz_from_Keras(channels, filter_size, strides, flatten, data_format, padding, floatx, decimal, helpers):
+    # xfail unavailable combinations
+    if floatx == 16 and keras.config.backend() == "torch":
+        pytest.xfail("Pytorch does not implement conv2d for float16")
+
     # filter_size, strides, flatten,
     if floatx == 16:
         decimal = 0
@@ -67,6 +70,10 @@ def test_toeplitz_from_Keras(channels, filter_size, strides, flatten, data_forma
 def test_toeplitz_from_Decomon(
     floatx, decimal, mode, channels, filter_size, strides, flatten, data_format, padding, helpers
 ):
+    # xfail unavailable combinations
+    if floatx == 16 and keras.config.backend() == "torch":
+        pytest.xfail("Pytorch does not implement conv2d for float16")
+
     if data_format == "channels_first" and not helpers.in_GPU_mode():
         pytest.skip("data format 'channels first' is possible only in GPU mode")