program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3304.5.2"}, {"coremlc-version", "3304.6.2"}, {"coremltools-component-torch", "2.1.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.0b1"}})]
{
    func main<ios16>(tensor<int32, [1]> full_sequence_length, tensor<int32, [1, 64]> input_ids) {
            tensor<int32, [1]> T = const()[name = tensor<string, []>("T"), val = tensor<int32, [1]>([64])];
            tensor<int32, []> x_1_axis_0 = const()[name = tensor<string, []>("x_1_axis_0"), val = tensor<int32, []>(0)];
            tensor<int32, []> x_1_batch_dims_0 = const()[name = tensor<string, []>("x_1_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [128256, 2048]> wte_weight_to_fp16 = const()[name = tensor<string, []>("wte_weight_to_fp16"), val = tensor<fp16, [128256, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp16, [1, 64, 2048]> x_1_cast_fp16 = gather(axis = x_1_axis_0, batch_dims = x_1_batch_dims_0, indices = input_ids, x = wte_weight_to_fp16)[name = tensor<string, []>("x_1_cast_fp16")];
            tensor<int32, [3]> x_perm_0 = const()[name = tensor<string, []>("x_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [4]> var_27 = const()[name = tensor<string, []>("op_27"), val = tensor<int32, [4]>([1, 2048, -1, 8])];
            tensor<fp16, [1, 2048, 64]> x_cast_fp16 = transpose(perm = x_perm_0, x = x_1_cast_fp16)[name = tensor<string, []>("transpose_1")];
            tensor<fp16, [1, 2048, 8, 8]> x = reshape(shape = var_27, x = x_cast_fp16)[name = tensor<string, []>("op_28_cast_fp16")];
            tensor<int32, [1]> pos_offset = sub(x = T, y = full_sequence_length)[name = tensor<string, []>("pos_offset")];
            tensor<int32, [64]> var_36 = const()[name = tensor<string, []>("op_36"), val = tensor<int32, [64]>([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63])];
            tensor<int32, [64]> input_pos_1 = sub(x = var_36, y = pos_offset)[name = tensor<string, []>("input_pos_1")];
            tensor<int32, [64]> var_44 = const()[name = tensor<string, []>("op_44"), val = tensor<int32, [64]>([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])];
            tensor<int32, [64]> input_pos = maximum(x = input_pos_1, y = var_44)[name = tensor<string, []>("input_pos")];
            tensor<int32, []> var_55 = const()[name = tensor<string, []>("op_55"), val = tensor<int32, []>(1)];
            tensor<int32, []> cos_batch_dims_0 = const()[name = tensor<string, []>("cos_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [64, 512]> var_54_to_fp16 = const()[name = tensor<string, []>("op_54_to_fp16"), val = tensor<fp16, [64, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525336704)))];
            tensor<fp16, [64, 64]> cos = gather(axis = var_55, batch_dims = cos_batch_dims_0, indices = input_pos, x = var_54_to_fp16)[name = tensor<string, []>("cos_cast_fp16")];
            tensor<int32, []> var_66 = const()[name = tensor<string, []>("op_66"), val = tensor<int32, []>(1)];
            tensor<int32, []> sin_batch_dims_0 = const()[name = tensor<string, []>("sin_batch_dims_0"), val = tensor<int32, []>(0)];
            tensor<fp16, [64, 512]> var_65_to_fp16 = const()[name = tensor<string, []>("op_65_to_fp16"), val = tensor<fp16, [64, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525402304)))];
            tensor<fp16, [64, 64]> sin = gather(axis = var_66, batch_dims = sin_batch_dims_0, indices = input_pos, x = var_65_to_fp16)[name = tensor<string, []>("sin_cast_fp16")];
            tensor<int32, [64, 1]> var_102 = const()[name = tensor<string, []>("op_102"), val = tensor<int32, [64, 1]>([[0], [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57], [58], [59], [60], [61], [62], [63]])];
            tensor<bool, [64, 1]> var_105 = less(x = var_102, y = pos_offset)[name = tensor<string, []>("op_105")];
            tensor<int32, [2]> var_105_after_broadcast_reps_0 = const()[name = tensor<string, []>("op_105_after_broadcast_reps_0"), val = tensor<int32, [2]>([1, 512])];
            tensor<bool, [64, 512]> var_105_after_broadcast = tile(reps = var_105_after_broadcast_reps_0, x = var_105)[name = tensor<string, []>("op_105_after_broadcast")];
            tensor<fp16, [64, 512]> all_mask_to_fp16 = const()[name = tensor<string, []>("all_mask_to_fp16"), val = tensor<fp16, [64, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525467904)))];
            tensor<fp16, [64, 512]> m_1_to_fp16 = const()[name = tensor<string, []>("m_1_to_fp16"), val = tensor<fp16, [64, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525533504)))];
            tensor<fp16, [64, 512]> m_3_cast_fp16 = select(a = all_mask_to_fp16, b = m_1_to_fp16, cond = var_105_after_broadcast)[name = tensor<string, []>("m_3_cast_fp16")];
            tensor<int32, [512]> var_115 = const()[name = tensor<string, []>("op_115"), val = tensor<int32, [512]>([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459, 460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479, 480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499, 500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511])];
            tensor<int32, []> var_116 = const()[name = tensor<string, []>("op_116"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> var_118 = sub(x = var_116, y = full_sequence_length)[name = tensor<string, []>("op_118")];
            tensor<bool, [512]> var_119 = less(x = var_115, y = var_118)[name = tensor<string, []>("op_119")];
            tensor<int32, [1]> expand_dims_0_axes_0 = const()[name = tensor<string, []>("expand_dims_0_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<bool, [1, 512]> expand_dims_0 = expand_dims(axes = expand_dims_0_axes_0, x = var_119)[name = tensor<string, []>("expand_dims_0")];
            tensor<int32, [2]> var_119_after_broadcast_reps_0 = const()[name = tensor<string, []>("op_119_after_broadcast_reps_0"), val = tensor<int32, [2]>([64, 1])];
            tensor<bool, [64, 512]> var_119_after_broadcast = tile(reps = var_119_after_broadcast_reps_0, x = expand_dims_0)[name = tensor<string, []>("op_119_after_broadcast")];
            tensor<fp16, [64, 512]> m_cast_fp16 = select(a = all_mask_to_fp16, b = m_3_cast_fp16, cond = var_119_after_broadcast)[name = tensor<string, []>("m_cast_fp16")];
            tensor<int32, [1]> var_122_axes_0 = const()[name = tensor<string, []>("op_122_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 64, 512]> var_122_cast_fp16 = expand_dims(axes = var_122_axes_0, x = m_cast_fp16)[name = tensor<string, []>("op_122_cast_fp16")];
            tensor<int32, [1]> mask_axes_0 = const()[name = tensor<string, []>("mask_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 64, 512]> mask_cast_fp16 = expand_dims(axes = mask_axes_0, x = var_122_cast_fp16)[name = tensor<string, []>("mask_cast_fp16")];
            tensor<int32, [4]> var_129 = const()[name = tensor<string, []>("op_129"), val = tensor<int32, [4]>([0, 3, 1, 2])];
            tensor<fp16, [1, 512, 1, 64]> mask = transpose(perm = var_129, x = mask_cast_fp16)[name = tensor<string, []>("transpose_0")];
        } -> (x, cos, sin, mask);
}