def forward(self, image):
size = image.size()
getitem = size[slice(2, None, None)]; size = None
model_model_backbone_patch_embed = self.model.model.backbone.patch_embed(image); image = None
size_1 = model_model_backbone_patch_embed.size(2)
size_2 = model_model_backbone_patch_embed.size(3)
flatten = model_model_backbone_patch_embed.flatten(2); model_model_backbone_patch_embed = None
flatten_activation_post_process_0 = self.flatten_activation_post_process_0(flatten); flatten = None
transpose = flatten_activation_post_process_0.transpose(1, 2); flatten_activation_post_process_0 = None
model_model_backbone_pos_drop = self.model.model.backbone.pos_drop(transpose); transpose = None
model_model_backbone_layers_0 = getattr(self.model.model.backbone.layers, "0")(model_model_backbone_pos_drop, size_1, size_2); model_model_backbone_pos_drop = size_1 = size_2 = None
getitem_1 = model_model_backbone_layers_0[0]
getitem_1_activation_post_process_0 = self.getitem_1_activation_post_process_0(getitem_1); getitem_1 = None
getitem_2 = model_model_backbone_layers_0[1]
getitem_2_activation_post_process_0 = self.getitem_2_activation_post_process_0(getitem_2); getitem_2 = None
getitem_3 = model_model_backbone_layers_0[2]
getitem_3_activation_post_process_0 = self.getitem_3_activation_post_process_0(getitem_3); getitem_3 = None
getitem_4 = model_model_backbone_layers_0[3]
getitem_5 = model_model_backbone_layers_0[4]
getitem_6 = model_model_backbone_layers_0[5]; model_model_backbone_layers_0 = None
model_model_backbone_norm0 = self.model.model.backbone.norm0(getitem_1_activation_post_process_0); getitem_1_activation_post_process_0 = None
model_model_backbone_norm0_activation_post_process_0 = self.model_model_backbone_norm0_activation_post_process_0(model_model_backbone_norm0); model_model_backbone_norm0 = None
view = model_model_backbone_norm0_activation_post_process_0.view(-1, getitem_2_activation_post_process_0, getitem_3_activation_post_process_0, 96); model_model_backbone_norm0_activation_post_process_0 = getitem_2_activation_post_process_0 = getitem_3_activation_post_process_0 = None
permute = view.permute(0, 3, 1, 2); view = None
contiguous = permute.contiguous(); permute = None
model_model_backbone_layers_1 = getattr(self.model.model.backbone.layers, "1")(getitem_4, getitem_5, getitem_6); getitem_4 = getitem_5 = getitem_6 = None
getitem_7 = model_model_backbone_layers_1[0]
getitem_7_activation_post_process_0 = self.getitem_7_activation_post_process_0(getitem_7); getitem_7 = None
getitem_8 = model_model_backbone_layers_1[1]
getitem_8_activation_post_process_0 = self.getitem_8_activation_post_process_0(getitem_8); getitem_8 = None
getitem_9 = model_model_backbone_layers_1[2]
getitem_9_activation_post_process_0 = self.getitem_9_activation_post_process_0(getitem_9); getitem_9 = None
getitem_10 = model_model_backbone_layers_1[3]
getitem_11 = model_model_backbone_layers_1[4]
getitem_12 = model_model_backbone_layers_1[5]; model_model_backbone_layers_1 = None
model_model_backbone_norm1 = self.model.model.backbone.norm1(getitem_7_activation_post_process_0); getitem_7_activation_post_process_0 = None
model_model_backbone_norm1_activation_post_process_0 = self.model_model_backbone_norm1_activation_post_process_0(model_model_backbone_norm1); model_model_backbone_norm1 = None
view_1 = model_model_backbone_norm1_activation_post_process_0.view(-1, getitem_8_activation_post_process_0, getitem_9_activation_post_process_0, 192); model_model_backbone_norm1_activation_post_process_0 = getitem_8_activation_post_process_0 = getitem_9_activation_post_process_0 = None
permute_1 = view_1.permute(0, 3, 1, 2); view_1 = None
contiguous_1 = permute_1.contiguous(); permute_1 = None
model_model_backbone_layers_2 = getattr(self.model.model.backbone.layers, "2")(getitem_10, getitem_11, getitem_12); getitem_10 = getitem_11 = getitem_12 = None
getitem_13 = model_model_backbone_layers_2[0]
getitem_13_activation_post_process_0 = self.getitem_13_activation_post_process_0(getitem_13); getitem_13 = None
getitem_14 = model_model_backbone_layers_2[1]
getitem_14_activation_post_process_0 = self.getitem_14_activation_post_process_0(getitem_14); getitem_14 = None
getitem_15 = model_model_backbone_layers_2[2]
getitem_15_activation_post_process_0 = self.getitem_15_activation_post_process_0(getitem_15); getitem_15 = None
getitem_16 = model_model_backbone_layers_2[3]
getitem_17 = model_model_backbone_layers_2[4]
getitem_18 = model_model_backbone_layers_2[5]; model_model_backbone_layers_2 = None
model_model_backbone_norm2 = self.model.model.backbone.norm2(getitem_13_activation_post_process_0); getitem_13_activation_post_process_0 = None
model_model_backbone_norm2_activation_post_process_0 = self.model_model_backbone_norm2_activation_post_process_0(model_model_backbone_norm2); model_model_backbone_norm2 = None
view_2 = model_model_backbone_norm2_activation_post_process_0.view(-1, getitem_14_activation_post_process_0, getitem_15_activation_post_process_0, 384); model_model_backbone_norm2_activation_post_process_0 = getitem_14_activation_post_process_0 = getitem_15_activation_post_process_0 = None
permute_2 = view_2.permute(0, 3, 1, 2); view_2 = None
contiguous_2 = permute_2.contiguous(); permute_2 = None
model_model_backbone_layers_3 = getattr(self.model.model.backbone.layers, "3")(getitem_16, getitem_17, getitem_18); getitem_16 = getitem_17 = getitem_18 = None
getitem_19 = model_model_backbone_layers_3[0]
getitem_19_activation_post_process_0 = self.getitem_19_activation_post_process_0(getitem_19); getitem_19 = None
getitem_20 = model_model_backbone_layers_3[1]
getitem_20_activation_post_process_0 = self.getitem_20_activation_post_process_0(getitem_20); getitem_20 = None
getitem_21 = model_model_backbone_layers_3[2]
getitem_21_activation_post_process_0 = self.getitem_21_activation_post_process_0(getitem_21); getitem_21 = None
getitem_22 = model_model_backbone_layers_3[3]
getitem_23 = model_model_backbone_layers_3[4]
getitem_24 = model_model_backbone_layers_3[5]; model_model_backbone_layers_3 = None
model_model_backbone_norm3 = self.model.model.backbone.norm3(getitem_19_activation_post_process_0); getitem_19_activation_post_process_0 = None
model_model_backbone_norm3_activation_post_process_0 = self.model_model_backbone_norm3_activation_post_process_0(model_model_backbone_norm3); model_model_backbone_norm3 = None
view_3 = model_model_backbone_norm3_activation_post_process_0.view(-1, getitem_20_activation_post_process_0, getitem_21_activation_post_process_0, 768); model_model_backbone_norm3_activation_post_process_0 = getitem_20_activation_post_process_0 = getitem_21_activation_post_process_0 = None
permute_3 = view_3.permute(0, 3, 1, 2); view_3 = None
contiguous_3 = permute_3.contiguous(); permute_3 = None
model_model_aspp1__conv1x1_weights = self.model.model.aspp1._conv1x1_weights
model_model_aspp1__conv1x1_weights_activation_post_process_0 = self.model_model_aspp1__conv1x1_weights_activation_post_process_0(model_model_aspp1__conv1x1_weights); model_model_aspp1__conv1x1_weights = None
conv2d = torch.conv2d(input = contiguous_3, weight = model_model_aspp1__conv1x1_weights_activation_post_process_0, padding = 'same', dilation = 1); model_model_aspp1__conv1x1_weights_activation_post_process_0 = None
conv2d_activation_post_process_0 = self.conv2d_activation_post_process_0(conv2d); conv2d = None
model_model_aspp1__bn_layers_0_weight = getattr(self.model.model.aspp1._bn_layers, "0").weight
model_model_aspp1__bn_layers_0_bias = getattr(self.model.model.aspp1._bn_layers, "0").bias
model_model_aspp1__bn_layers_0_running_mean = getattr(self.model.model.aspp1._bn_layers, "0").running_mean
model_model_aspp1__bn_layers_0_running_var = getattr(self.model.model.aspp1._bn_layers, "0").running_var
batch_norm = torch.nn.functional.batch_norm(conv2d_activation_post_process_0, model_model_aspp1__bn_layers_0_running_mean, model_model_aspp1__bn_layers_0_running_var, weight = model_model_aspp1__bn_layers_0_weight, bias = model_model_aspp1__bn_layers_0_bias, training = False, momentum = 0.1, eps = 1e-05); conv2d_activation_post_process_0 = model_model_aspp1__bn_layers_0_running_mean = model_model_aspp1__bn_layers_0_running_var = model_model_aspp1__bn_layers_0_weight = model_model_aspp1__bn_layers_0_bias = None
relu = torch.relu(batch_norm); batch_norm = None
relu_activation_post_process_0 = self.relu_activation_post_process_0(relu)
model_model_aspp1__conv2d_weights = self.model.model.aspp1._conv2d_weights
model_model_aspp1__conv2d_weights_activation_post_process_0 = self.model_model_aspp1__conv2d_weights_activation_post_process_0(model_model_aspp1__conv2d_weights); model_model_aspp1__conv2d_weights = None
conv2d_1 = torch.conv2d(input = contiguous_3, weight = model_model_aspp1__conv2d_weights_activation_post_process_0, padding = 'same', dilation = 6)
conv2d_1_activation_post_process_0 = self.conv2d_1_activation_post_process_0(conv2d_1); conv2d_1 = None
model_model_aspp1__bn_layers_1_weight = getattr(self.model.model.aspp1._bn_layers, "1").weight
model_model_aspp1__bn_layers_1_bias = getattr(self.model.model.aspp1._bn_layers, "1").bias
model_model_aspp1__bn_layers_1_running_mean = getattr(self.model.model.aspp1._bn_layers, "1").running_mean
model_model_aspp1__bn_layers_1_running_var = getattr(self.model.model.aspp1._bn_layers, "1").running_var
batch_norm_1 = torch.nn.functional.batch_norm(conv2d_1_activation_post_process_0, model_model_aspp1__bn_layers_1_running_mean, model_model_aspp1__bn_layers_1_running_var, weight = model_model_aspp1__bn_layers_1_weight, bias = model_model_aspp1__bn_layers_1_bias, training = False, momentum = 0.1, eps = 1e-05); conv2d_1_activation_post_process_0 = model_model_aspp1__bn_layers_1_running_mean = model_model_aspp1__bn_layers_1_running_var = model_model_aspp1__bn_layers_1_weight = model_model_aspp1__bn_layers_1_bias = None
relu_1 = torch.relu(batch_norm_1); batch_norm_1 = None
relu_1_activation_post_process_0 = self.relu_1_activation_post_process_0(relu_1); relu_1 = None
conv2d_2 = torch.conv2d(input = contiguous_3, weight = model_model_aspp1__conv2d_weights_activation_post_process_0, padding = 'same', dilation = 12)
conv2d_2_activation_post_process_0 = self.conv2d_2_activation_post_process_0(conv2d_2); conv2d_2 = None
model_model_aspp1__bn_layers_2_weight = getattr(self.model.model.aspp1._bn_layers, "2").weight
model_model_aspp1__bn_layers_2_bias = getattr(self.model.model.aspp1._bn_layers, "2").bias
model_model_aspp1__bn_layers_2_running_mean = getattr(self.model.model.aspp1._bn_layers, "2").running_mean
model_model_aspp1__bn_layers_2_running_var = getattr(self.model.model.aspp1._bn_layers, "2").running_var
batch_norm_2 = torch.nn.functional.batch_norm(conv2d_2_activation_post_process_0, model_model_aspp1__bn_layers_2_running_mean, model_model_aspp1__bn_layers_2_running_var, weight = model_model_aspp1__bn_layers_2_weight, bias = model_model_aspp1__bn_layers_2_bias, training = False, momentum = 0.1, eps = 1e-05); conv2d_2_activation_post_process_0 = model_model_aspp1__bn_layers_2_running_mean = model_model_aspp1__bn_layers_2_running_var = model_model_aspp1__bn_layers_2_weight = model_model_aspp1__bn_layers_2_bias = None
relu_2 = torch.relu(batch_norm_2); batch_norm_2 = None
relu_2_activation_post_process_0 = self.relu_2_activation_post_process_0(relu_2); relu_2 = None
conv2d_3 = torch.conv2d(input = contiguous_3, weight = model_model_aspp1__conv2d_weights_activation_post_process_0, padding = 'same', dilation = 18); model_model_aspp1__conv2d_weights_activation_post_process_0 = None
conv2d_3_activation_post_process_0 = self.conv2d_3_activation_post_process_0(conv2d_3); conv2d_3 = None
model_model_aspp1__bn_layers_3_weight = getattr(self.model.model.aspp1._bn_layers, "3").weight
model_model_aspp1__bn_layers_3_bias = getattr(self.model.model.aspp1._bn_layers, "3").bias
model_model_aspp1__bn_layers_3_running_mean = getattr(self.model.model.aspp1._bn_layers, "3").running_mean
model_model_aspp1__bn_layers_3_running_var = getattr(self.model.model.aspp1._bn_layers, "3").running_var
batch_norm_3 = torch.nn.functional.batch_norm(conv2d_3_activation_post_process_0, model_model_aspp1__bn_layers_3_running_mean, model_model_aspp1__bn_layers_3_running_var, weight = model_model_aspp1__bn_layers_3_weight, bias = model_model_aspp1__bn_layers_3_bias, training = False, momentum = 0.1, eps = 1e-05); conv2d_3_activation_post_process_0 = model_model_aspp1__bn_layers_3_running_mean = model_model_aspp1__bn_layers_3_running_var = model_model_aspp1__bn_layers_3_weight = model_model_aspp1__bn_layers_3_bias = None
relu_3 = torch.relu(batch_norm_3); batch_norm_3 = None
relu_3_activation_post_process_0 = self.relu_3_activation_post_process_0(relu_3); relu_3 = None
model_model_aspp1_global_avg_pool_0 = getattr(self.model.model.aspp1.global_avg_pool, "0")(contiguous_3); contiguous_3 = None
model_model_aspp1_global_avg_pool_1 = getattr(self.model.model.aspp1.global_avg_pool, "1")(model_model_aspp1_global_avg_pool_0); model_model_aspp1_global_avg_pool_0 = None
model_model_aspp1_global_avg_pool_1_activation_post_process_0 = self.model_model_aspp1_global_avg_pool_1_activation_post_process_0(model_model_aspp1_global_avg_pool_1); model_model_aspp1_global_avg_pool_1 = None
model_model_aspp1_global_avg_pool_2_weight = getattr(self.model.model.aspp1.global_avg_pool, "2").weight
model_model_aspp1_global_avg_pool_2_bias = getattr(self.model.model.aspp1.global_avg_pool, "2").bias
model_model_aspp1_global_avg_pool_2_running_mean = getattr(self.model.model.aspp1.global_avg_pool, "2").running_mean
model_model_aspp1_global_avg_pool_2_running_var = getattr(self.model.model.aspp1.global_avg_pool, "2").running_var
batch_norm_4 = torch.nn.functional.batch_norm(model_model_aspp1_global_avg_pool_1_activation_post_process_0, model_model_aspp1_global_avg_pool_2_running_mean, model_model_aspp1_global_avg_pool_2_running_var, weight = model_model_aspp1_global_avg_pool_2_weight, bias = model_model_aspp1_global_avg_pool_2_bias, training = False, momentum = 0.1, eps = 1e-05); model_model_aspp1_global_avg_pool_1_activation_post_process_0 = model_model_aspp1_global_avg_pool_2_running_mean = model_model_aspp1_global_avg_pool_2_running_var = model_model_aspp1_global_avg_pool_2_weight = model_model_aspp1_global_avg_pool_2_bias = None
batch_norm_4_activation_post_process_0 = self.batch_norm_4_activation_post_process_0(batch_norm_4); batch_norm_4 = None
model_model_aspp1_global_avg_pool_3 = getattr(self.model.model.aspp1.global_avg_pool, "3")(batch_norm_4_activation_post_process_0); batch_norm_4_activation_post_process_0 = None
size_3 = relu.size(); relu = None
getitem_25 = size_3[slice(2, None, None)]; size_3 = None
interpolate = torch.nn.functional.interpolate(model_model_aspp1_global_avg_pool_3, size = getitem_25, scale_factor = None, mode = 'bilinear', align_corners = True, recompute_scale_factor = None); model_model_aspp1_global_avg_pool_3 = getitem_25 = None
cat = torch.cat([relu_activation_post_process_0, relu_1_activation_post_process_0, relu_2_activation_post_process_0, relu_3_activation_post_process_0, interpolate], dim = 1); relu_activation_post_process_0 = relu_1_activation_post_process_0 = relu_2_activation_post_process_0 = relu_3_activation_post_process_0 = interpolate = None
cat_activation_post_process_0 = self.cat_activation_post_process_0(cat); cat = None
model_model_aspp1_conv_out = self.model.model.aspp1.conv_out(cat_activation_post_process_0); cat_activation_post_process_0 = None
model_model_aspp1_conv_out_activation_post_process_0 = self.model_model_aspp1_conv_out_activation_post_process_0(model_model_aspp1_conv_out); model_model_aspp1_conv_out = None
model_model_aspp1_bn_out_weight = self.model.model.aspp1.bn_out.weight
model_model_aspp1_bn_out_bias = self.model.model.aspp1.bn_out.bias
model_model_aspp1_bn_out_running_mean = self.model.model.aspp1.bn_out.running_mean
model_model_aspp1_bn_out_running_var = self.model.model.aspp1.bn_out.running_var
batch_norm_5 = torch.nn.functional.batch_norm(model_model_aspp1_conv_out_activation_post_process_0, model_model_aspp1_bn_out_running_mean, model_model_aspp1_bn_out_running_var, weight = model_model_aspp1_bn_out_weight, bias = model_model_aspp1_bn_out_bias, training = False, momentum = 0.1, eps = 1e-05); model_model_aspp1_conv_out_activation_post_process_0 = model_model_aspp1_bn_out_running_mean = model_model_aspp1_bn_out_running_var = model_model_aspp1_bn_out_weight = model_model_aspp1_bn_out_bias = None
batch_norm_5_activation_post_process_0 = self.batch_norm_5_activation_post_process_0(batch_norm_5); batch_norm_5 = None
model_model_aspp1_relu = self.model.model.aspp1.relu(batch_norm_5_activation_post_process_0); batch_norm_5_activation_post_process_0 = None
model_model_aspp1_dropout = self.model.model.aspp1.dropout(model_model_aspp1_relu); model_model_aspp1_relu = None
model_model_dec_cn_1_layer_0 = getattr(self.model.model.dec_cn_1.layer, "0")(contiguous_2); contiguous_2 = None
model_model_dec_cn_1_layer_0_activation_post_process_0 = self.model_model_dec_cn_1_layer_0_activation_post_process_0(model_model_dec_cn_1_layer_0); model_model_dec_cn_1_layer_0 = None
model_model_dec_cn_2_layer_0 = getattr(self.model.model.dec_cn_2.layer, "0")(contiguous_1); contiguous_1 = None
model_model_dec_cn_2_layer_0_activation_post_process_0 = self.model_model_dec_cn_2_layer_0_activation_post_process_0(model_model_dec_cn_2_layer_0); model_model_dec_cn_2_layer_0 = None
model_model_dec_cn_3_layer_0 = getattr(self.model.model.dec_cn_3.layer, "0")(contiguous); contiguous = None
model_model_dec_cn_3_layer_0_activation_post_process_0 = self.model_model_dec_cn_3_layer_0_activation_post_process_0(model_model_dec_cn_3_layer_0); model_model_dec_cn_3_layer_0 = None
size_4 = model_model_dec_cn_1_layer_0_activation_post_process_0.size()
getitem_26 = size_4[slice(2, None, None)]; size_4 = None
interpolate_1 = torch.nn.functional.interpolate(model_model_aspp1_dropout, size = getitem_26, scale_factor = None, mode = 'nearest', align_corners = None, recompute_scale_factor = None); model_model_aspp1_dropout = getitem_26 = None
cat_1 = torch.cat([model_model_dec_cn_1_layer_0_activation_post_process_0, interpolate_1], dim = 1); model_model_dec_cn_1_layer_0_activation_post_process_0 = interpolate_1 = None
cat_1_activation_post_process_0 = self.cat_1_activation_post_process_0(cat_1); cat_1 = None
model_model_dec_cn_1_1_layer_0 = getattr(self.model.model.dec_cn_1_1.layer, "0")(cat_1_activation_post_process_0); cat_1_activation_post_process_0 = None
model_model_dec_cn_1_1_layer_0_activation_post_process_0 = self.model_model_dec_cn_1_1_layer_0_activation_post_process_0(model_model_dec_cn_1_1_layer_0); model_model_dec_cn_1_1_layer_0 = None
size_5 = model_model_dec_cn_2_layer_0_activation_post_process_0.size()
getitem_27 = size_5[slice(2, None, None)]; size_5 = None
interpolate_2 = torch.nn.functional.interpolate(model_model_dec_cn_1_1_layer_0_activation_post_process_0, size = getitem_27, scale_factor = None, mode = 'nearest', align_corners = None, recompute_scale_factor = None); model_model_dec_cn_1_1_layer_0_activation_post_process_0 = getitem_27 = None
cat_2 = torch.cat([model_model_dec_cn_2_layer_0_activation_post_process_0, interpolate_2], dim = 1); model_model_dec_cn_2_layer_0_activation_post_process_0 = interpolate_2 = None
cat_2_activation_post_process_0 = self.cat_2_activation_post_process_0(cat_2); cat_2 = None
model_model_dec_cn_2_1_layer_0 = getattr(self.model.model.dec_cn_2_1.layer, "0")(cat_2_activation_post_process_0); cat_2_activation_post_process_0 = None
model_model_dec_cn_2_1_layer_0_activation_post_process_0 = self.model_model_dec_cn_2_1_layer_0_activation_post_process_0(model_model_dec_cn_2_1_layer_0); model_model_dec_cn_2_1_layer_0 = None
size_6 = model_model_dec_cn_3_layer_0_activation_post_process_0.size()
getitem_28 = size_6[slice(2, None, None)]; size_6 = None
interpolate_3 = torch.nn.functional.interpolate(model_model_dec_cn_2_1_layer_0_activation_post_process_0, size = getitem_28, scale_factor = None, mode = 'nearest', align_corners = None, recompute_scale_factor = None); model_model_dec_cn_2_1_layer_0_activation_post_process_0 = getitem_28 = None
cat_3 = torch.cat([model_model_dec_cn_3_layer_0_activation_post_process_0, interpolate_3], dim = 1); model_model_dec_cn_3_layer_0_activation_post_process_0 = interpolate_3 = None
cat_3_activation_post_process_0 = self.cat_3_activation_post_process_0(cat_3); cat_3 = None
model_model_dec_cn_3_1_layer_0 = getattr(self.model.model.dec_cn_3_1.layer, "0")(cat_3_activation_post_process_0); cat_3_activation_post_process_0 = None
model_model_dec_cn_3_1_layer_0_activation_post_process_0 = self.model_model_dec_cn_3_1_layer_0_activation_post_process_0(model_model_dec_cn_3_1_layer_0); model_model_dec_cn_3_1_layer_0 = None
model_model_head_0_layer_0 = getattr(getattr(self.model.model.head, "0").layer, "0")(model_model_dec_cn_3_1_layer_0_activation_post_process_0); model_model_dec_cn_3_1_layer_0_activation_post_process_0 = None
model_model_head_0_layer_0_activation_post_process_0 = self.model_model_head_0_layer_0_activation_post_process_0(model_model_head_0_layer_0); model_model_head_0_layer_0 = None
model_model_head_1_layer_0 = getattr(getattr(self.model.model.head, "1").layer, "0")(model_model_head_0_layer_0_activation_post_process_0); model_model_head_0_layer_0_activation_post_process_0 = None
model_model_head_1_layer_0_activation_post_process_0 = self.model_model_head_1_layer_0_activation_post_process_0(model_model_head_1_layer_0); model_model_head_1_layer_0 = None
model_model_head_2 = getattr(self.model.model.head, "2")(model_model_head_1_layer_0_activation_post_process_0); model_model_head_1_layer_0_activation_post_process_0 = None
model_model_head_2_activation_post_process_0 = self.model_model_head_2_activation_post_process_0(model_model_head_2); model_model_head_2 = None
interpolate_4 = torch.nn.functional.interpolate(model_model_head_2_activation_post_process_0, size = getitem, scale_factor = None, mode = 'bilinear', align_corners = None, recompute_scale_factor = None); model_model_head_2_activation_post_process_0 = getitem = None
return interpolate_4
